diff --git a/.github/workflows/env_test.yml b/.github/workflows/env_test.yml
new file mode 100644
index 0000000..238ea17
--- /dev/null
+++ b/.github/workflows/env_test.yml
@@ -0,0 +1,26 @@
+name: Environment Test
+
+on: [push, workflow_dispatch]
+
+jobs:
+  build:
+    # continue-on-error: true
+    strategy:
+      matrix:
+        os: [ubuntu-20.04, ubuntu-22.04, windows-latest, macos-12, macos-11]
+        python-version: ["3.8", "3.9", "3.10"]
+    runs-on: ${{ matrix.os }}
+    steps:
+      - uses: actions/checkout@v3
+      - uses: actions/setup-python@v4
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip poetry
+          poetry install
+      - name: Run test
+        env:
+          NAS_CREDS: ${{ secrets.NAS_CREDS }}
+        run: |
+          poetry run python -m pytest pyha_tests
\ No newline at end of file
diff --git a/.gitignore b/.gitignore
index 8130b4a..6297221 100644
--- a/.gitignore
+++ b/.gitignore
@@ -27,4 +27,286 @@ mixed_bird_manual.csv
 
 
 !PyHa_Tutorial.ipynb
-!ScreamingPiha_Manual_Labels.csv
\ No newline at end of file
+!ScreamingPiha_Manual_Labels.csv
+
+# Created by https://www.toptal.com/developers/gitignore/api/jupyternotebooks,python,linux,macos,windows,visualstudiocode
+# Edit at https://www.toptal.com/developers/gitignore?templates=jupyternotebooks,python,linux,macos,windows,visualstudiocode
+
+### JupyterNotebooks ###
+# gitignore template for Jupyter Notebooks
+# website: http://jupyter.org/
+
+.ipynb_checkpoints
+*/.ipynb_checkpoints/*
+
+# IPython
+profile_default/
+ipython_config.py
+
+# Remove previous ipynb_checkpoints
+#   git rm -r .ipynb_checkpoints/
+
+### Linux ###
+*~
+
+# temporary files which can be created if a process still has a handle open of a deleted file
+.fuse_hidden*
+
+# KDE directory preferences
+.directory
+
+# Linux trash folder which might appear on any partition or disk
+.Trash-*
+
+# .nfs files are created when an open file is removed but is still being accessed
+.nfs*
+
+### macOS ###
+# General
+.DS_Store
+.AppleDouble
+.LSOverride
+
+# Icon must end with two \r
+Icon
+
+
+# Thumbnails
+._*
+
+# Files that might appear in the root of a volume
+.DocumentRevisions-V100
+.fseventsd
+.Spotlight-V100
+.TemporaryItems
+.Trashes
+.VolumeIcon.icns
+.com.apple.timemachine.donotpresent
+
+# Directories potentially created on remote AFP share
+.AppleDB
+.AppleDesktop
+Network Trash Folder
+Temporary Items
+.apdisk
+
+### macOS Patch ###
+# iCloud generated files
+*.icloud
+
+### Python ###
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+
+# IPython
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+### Python Patch ###
+# Poetry local configuration file - https://python-poetry.org/docs/configuration/#local-configuration
+poetry.toml
+
+# ruff
+.ruff_cache/
+
+# LSP config files
+pyrightconfig.json
+
+### VisualStudioCode ###
+.vscode/*
+!.vscode/settings.json
+!.vscode/tasks.json
+!.vscode/launch.json
+!.vscode/extensions.json
+!.vscode/*.code-snippets
+
+# Local History for Visual Studio Code
+.history/
+
+# Built Visual Studio Code Extensions
+*.vsix
+
+### VisualStudioCode Patch ###
+# Ignore all local history of files
+.history
+.ionide
+
+### Windows ###
+# Windows thumbnail cache files
+Thumbs.db
+Thumbs.db:encryptable
+ehthumbs.db
+ehthumbs_vista.db
+
+# Dump file
+*.stackdump
+
+# Folder config file
+[Dd]esktop.ini
+
+# Recycle Bin used on file shares
+$RECYCLE.BIN/
+
+# Windows Installer files
+*.cab
+*.msi
+*.msix
+*.msm
+*.msp
+
+# Windows shortcuts
+*.lnk
+
+# End of https://www.toptal.com/developers/gitignore/api/jupyternotebooks,python,linux,macos,windows,visualstudiocode
+credentials.json
diff --git a/.vscode/settings.json b/.vscode/settings.json
new file mode 100644
index 0000000..dc4854c
--- /dev/null
+++ b/.vscode/settings.json
@@ -0,0 +1,7 @@
+{
+    "python.testing.pytestArgs": [
+        "pyha_tests"
+    ],
+    "python.testing.unittestEnabled": false,
+    "python.testing.pytestEnabled": true
+}
\ No newline at end of file
diff --git a/PyHa/IsoAutio.py b/PyHa/IsoAutio.py
index ce8b953..732e79d 100644
--- a/PyHa/IsoAutio.py
+++ b/PyHa/IsoAutio.py
@@ -12,7 +12,7 @@
 from math import ceil
 from copy import deepcopy
 from sys import exit
-
+import logging
 
 def checkVerbose(
     errorMessage, 
@@ -966,6 +966,7 @@ def generate_automated_labels_microfaune(
         except KeyboardInterrupt:
             exit("Keyboard interrupt")
         except BaseException as e:
+            checkVerbose(e, isolation_parameters)
             checkVerbose("Error in detection, skipping" + audio_file, isolation_parameters)
             continue
         
@@ -989,11 +990,11 @@ def generate_automated_labels_microfaune(
             if annotations.empty:
                 annotations = new_entry
             else:
-                annotations = annotations.append(new_entry)
+                annotations = pd.concat([annotations, new_entry])
         except KeyboardInterrupt:
             exit("Keyboard interrupt")
         except BaseException as e:
-
+            checkVerbose(e, isolation_parameters)
             checkVerbose("Error in isolating bird calls from" + audio_file, isolation_parameters)
 
             continue
@@ -1040,6 +1041,7 @@ def generate_automated_labels_tweetynet(
     Returns:
         Dataframe of automated labels for the audio clips in audio_dir.
     """
+    logger = logging.getLogger("TweetyNet Autogenerated Labels")
 
     assert isinstance(audio_dir,str)
     assert isinstance(isolation_parameters,dict)
@@ -1070,7 +1072,8 @@ def generate_automated_labels_tweetynet(
             SIGNAL = SIGNAL * 32768
         except KeyboardInterrupt:
             exit("Keyboard interrupt")
-        except BaseException:
+        except Exception as exp:
+            logger.exception(f"Failed to load {audio_file}, parameters: {isolation_parameters}")
             checkVerbose("Failed to load " + audio_file, isolation_parameters)
             continue
             
@@ -1083,8 +1086,9 @@ def generate_automated_labels_tweetynet(
                 SAMPLE_RATE = normalized_sample_rate
         except KeyboardInterrupt:
             exit("Keyboard interrupt")
-        except:
+        except Exception as exc:
             checkVerbose("Failed to Downsample " + audio_file, isolation_parameters)
+            logger.exception(f'Failed to downsample {audio_file}, parameters: {isolation_parameters}')
             
         # convert stereo to mono if needed
         # Might want to compare to just taking the first set of data.
@@ -1099,6 +1103,7 @@ def generate_automated_labels_tweetynet(
         except BaseException as e:
             checkVerbose("Error in detection, skipping " + audio_file, isolation_parameters)
             print(e)
+            logger.exception(f'Error in detection, skipping {audio_file}, parameters: {isolation_parameters}')
             continue
            
         try:
@@ -1126,12 +1131,12 @@ def generate_automated_labels_tweetynet(
             if annotations.empty:
                 annotations = new_entry
             else:
-                annotations = annotations.append(new_entry)
+                annotations = pd.concat([annotations, new_entry])
         except KeyboardInterrupt:
             exit("Keyboard interrupt")
         except BaseException as e:
             checkVerbose("Error in isolating bird calls from " + audio_file, isolation_parameters)
-            print(e)
+            logger.exception(f"Error in isolating bird calls from {audio_file}")
             continue
     # Quick fix to indexing
     annotations.reset_index(inplace=True, drop=True)
diff --git a/PyHa/__init__.py b/PyHa/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/PyHa/birdnet_lite/analyze.py b/PyHa/birdnet_lite/analyze.py
index 863f0e2..20ec2d1 100644
--- a/PyHa/birdnet_lite/analyze.py
+++ b/PyHa/birdnet_lite/analyze.py
@@ -15,6 +15,8 @@
 import time
 import pandas as pd
 from sys import exit
+import logging
+from pathlib import Path
 
 def loadModel():
 
@@ -83,13 +85,14 @@ def splitSignal(sig, rate, overlap, seconds=3.0, minlen=1.5):
 def readAudioData(path, overlap, sample_rate=48000):
 
     print('READING AUDIO DATA...', end=' ', flush=True)
-
-    # Open file with librosa (uses ffmpeg or libav)
+    print("Path: ", path)
+    # Open file with librosa (uses ffmanaeg or libav)
     try:
         sig, rate = librosa.load(path, sr=sample_rate, mono=True, res_type='kaiser_fast')
         clip_length = librosa.get_duration(y=sig, sr=rate)
-    except:
-        return 0
+    except Exception as e:
+        print(e)
+        return (0, 0)
     # Split audio into 3-second chunks
     chunks = splitSignal(sig, rate, overlap)
 
@@ -261,14 +264,15 @@ def analyze(audio_path, output_path = None, lat=-1, lon=-1, week=-1, overlap=0.0
                 if audioData == 0:
                     continue
                 detections = analyzeAudioData(audioData, lat, lon, week, sensitivity, overlap, interpreter,  num_predictions)
-                output_metadata['FOLDER']  = os.path.join('.', os.path.relpath(os.path.split(datafile)[0], os.getcwd())) + os.path.sep
+                output_metadata['FOLDER']  = Path(datafile).resolve().as_posix()
                 output_metadata['IN FILE'] = os.path.split(datafile)[1]
                 output_metadata['CLIP LENGTH'] = clip_length
                 df = writeResultsToDf(df, detections, min_conf, output_metadata)
             except KeyboardInterrupt:
                 exit("Keyboard interrupt")
-            except:
+            except Exception as exc:
                 print("Error in processing file: {}".format(datafile)) 
+                logging.exception(f"Error in processing file: {datafile}")
         if output_path is None:
             output_file = os.path.join(audio_path, 'result.csv')
             output_file = os.path.abspath(output_file)
diff --git a/PyHa/microfaune_package/microfaune/audio.py b/PyHa/microfaune_package/microfaune/audio.py
index c1af3c0..dd6f075 100644
--- a/PyHa/microfaune_package/microfaune/audio.py
+++ b/PyHa/microfaune_package/microfaune/audio.py
@@ -124,7 +124,7 @@ def create_spec(data, fs, n_mels=32, n_fft=2048, hop_len=1024):
     """
     # Calculate spectrogram
     S = librosa.feature.melspectrogram(
-      data, sr=fs, n_fft=n_fft, hop_length=hop_len, n_mels=n_mels)
+    y=data, sr=fs, n_fft=n_fft, hop_length=hop_len, n_mels=n_mels)
     S = S.astype(np.float32)
 
     # Convert power to dB
diff --git a/PyHa/statistics.py b/PyHa/statistics.py
index bfd3066..72ec75d 100644
--- a/PyHa/statistics.py
+++ b/PyHa/statistics.py
@@ -263,7 +263,7 @@ def automated_labeling_statistics(
                 if statistics_df.empty:
                     statistics_df = clip_stats_df
                 else:
-                    statistics_df = statistics_df.append(clip_stats_df)
+                    statistics_df = pd.concat([statistics_df,clip_stats_df])
             elif stats_type == "IoU":
                 IoU_Matrix = clip_IoU(clip_automated_df, clip_manual_df)
                 clip_stats_df = matrix_IoU_Scores(
@@ -271,17 +271,17 @@ def automated_labeling_statistics(
                 if statistics_df.empty:
                     statistics_df = clip_stats_df
                 else:
-                    statistics_df = statistics_df.append(clip_stats_df)
+                    statistics_df = pd.concat([statistics_df, clip_stats_df])
         except BaseException as e:
             num_errors += 1
             #print("Something went wrong with: " + clip)
-            #print(e)
+            print(e)
             continue
         if num_processed % 50 == 0:
             print("Processed", num_processed, "clips in", int((time.time() - start_time) * 10) / 10.0, 'seconds')
             start_time = time.time()
     if num_errors > 0:
-        checkVerbose("Something went wrong with" + num_errors + "clips out of" + str(len(clips)) + "clips", verbose)
+        checkVerbose(f"Something went wrong with {num_errors} clips out of {len(clips)} clips", verbose)
     statistics_df.reset_index(inplace=True, drop=True)
     return statistics_df
 
@@ -751,7 +751,7 @@ def dataset_Catch(automated_df, manual_df):
         if manual_df_with_Catch.empty:
             manual_df_with_Catch = clip_manual_df
         else:
-            manual_df_with_Catch = manual_df_with_Catch.append(clip_manual_df)
+            manual_df_with_Catch = pd.concat([manual_df_with_Catch,clip_manual_df])
     # Resetting the indices
     manual_df_with_Catch.reset_index(inplace=True, drop=True)
     return manual_df_with_Catch
@@ -825,7 +825,7 @@ def clip_statistics(
             clip_statistics = automated_labeling_statistics(temp_automated_class_df, temp_manual_class_df, stats_type = stats_type, threshold = threshold)
         else:
             temp_df = automated_labeling_statistics(temp_automated_class_df, temp_manual_class_df, stats_type = stats_type, threshold = threshold)
-            clip_statistics = clip_statistics.append(temp_df)
+            clip_statistics = pd.concat([clip_statistics,temp_df])
     clip_statistics.reset_index(inplace=True,drop=True)
     return clip_statistics
 
@@ -860,6 +860,6 @@ def class_statistics(clip_statistics):
             class_statistics = global_statistics(class_df, manual_id = class_)
         else:
             temp_df = global_statistics(class_df, manual_id = class_)
-            class_statistics = class_statistics.append(temp_df)
+            class_statistics = pd.concat([class_statistics,temp_df])
     class_statistics.reset_index(inplace=True,drop=True)
     return class_statistics
diff --git a/PyHa/tweetynet_package/tweetynet/TweetyNetModel.py b/PyHa/tweetynet_package/tweetynet/TweetyNetModel.py
index 013cd61..5627194 100644
--- a/PyHa/tweetynet_package/tweetynet/TweetyNetModel.py
+++ b/PyHa/tweetynet_package/tweetynet/TweetyNetModel.py
@@ -111,7 +111,7 @@ def predict(self, test_dataset, model_weights=None, norm=False):
                 bins = st_time + (int(uids[0].split("_")[0])*window_size)
                 d = {"uid": uids[0], "pred": pred, "label": labels, "time_bins": bins}
                 new_preds = pd.DataFrame(d)
-                predictions = predictions.append(new_preds)
+                predictions = pd.concat([predictions, new_preds])
 
         if norm:
             local_score = self.normalize(local_score, 0, 1)
diff --git a/README.md b/README.md
index 2d2e0b2..eb6a18d 100644
--- a/README.md
+++ b/README.md
@@ -17,11 +17,15 @@ PyHa = Python + Piha (referring to a bird species of our interest known as the s
 ## Installation and Setup
 1. Navigate to a desired folder and clone the repository onto your local machine. `git clone https://github.com/UCSD-E4E/PyHa.git`
 - If you wish to reduce the size of the repository on your local machine you can alternatively use `git clone https://github.com/UCSD-E4E/PyHa.git --depth 1` which will only install the most up-to-date version of the repo without its history.
-2. Install [Miniconda](https://docs.conda.io/en/latest/miniconda.html) or [Miniforge](https://github.com/conda-forge/miniforge).
-3. Install the conda environment by running `conda env create --file conda_environments/{filename}`, where `filename` is the name of the yaml containing the environment for your OS.
-4. Run `conda activate species-id` to activate the conda environment used to develop the package.
-5. Here you can download the Xeno-canto Screaming Piha test set used in our demos: https://drive.google.com/drive/u/0/folders/1lIweB8rF9JZhu6imkuTg_No0i04ClDh1
-6. Run `jupyter notebook` while in the proper folder to activate the PyHa_Tutorial.ipynb notebook and make sure PyHa is running properly. Make sure the paths are properly aligned to the TEST folder in the notebook as well as in the ScreamingPiha_Manual_Labels.csv file
+2. Install Python 3.8, Python 3.9, or Python 3.10
+3. Create a `venv` by running `python3.x -m venv .venv` where `python3.x` is the appropriate python.
+4. Activate the `venv` with the following commands:
+  - Windows: `.venv\Scripts\activate`
+  - macOS/Linux: `source .venv/bin/activate`
+5. Install the build tools: `python -m pip install --upgrade pip poetry`
+6. Install the environment: `poetry install`
+7. Here you can download the Xeno-canto Screaming Piha test set used in our demos: https://drive.google.com/drive/u/0/folders/1lIweB8rF9JZhu6imkuTg_No0i04ClDh1
+8. Run `jupyter notebook` while in the proper folder to activate the PyHa_Tutorial.ipynb notebook and make sure PyHa is running properly. Make sure the paths are properly aligned to the TEST folder in the notebook as well as in the ScreamingPiha_Manual_Labels.csv file
 
 ## Functions
 ![design](https://user-images.githubusercontent.com/44332326/126560960-e9816f7e-c31b-40ee-804d-6947053323c2.png)
diff --git a/conda_environments/environment_MacOS_BigSur.11.4.yml b/conda_environments/environment_MacOS_BigSur.11.4.yml
deleted file mode 100644
index cea3ec3..0000000
--- a/conda_environments/environment_MacOS_BigSur.11.4.yml
+++ /dev/null
@@ -1,207 +0,0 @@
-name: species-id
-channels:
-  - conda-forge
-  - defaults
-dependencies:
-  - absl-py=0.12.0=pyhd8ed1ab_0
-  - appdirs=1.4.4=pyh9f0ad1d_0
-  - argon2-cffi=20.1.0=py37hf967b71_2
-  - astor=0.8.1=pyh9f0ad1d_0
-  - async_generator=1.10=py_0
-  - attrs=20.3.0=pyhd3deb0d_0
-  - audioread=2.1.9=py37hf985489_0
-  - backcall=0.2.0=pyh9f0ad1d_0
-  - backports=1.0=py_2
-  - backports.functools_lru_cache=1.6.3=pyhd8ed1ab_0
-  - bleach=3.3.0=pyh44b312d_0
-  - brotlipy=0.7.0=py37hf967b71_1001
-  - bzip2=1.0.8=h0d85af4_4
-  - c-ares=1.17.1=h0d85af4_1
-  - ca-certificates=2020.12.5=h033912b_0
-  - cached-property=1.5.2=hd8ed1ab_1
-  - cached_property=1.5.2=pyha770c72_1
-  - certifi=2020.12.5=py38h50d1736_1
-  - cffi=1.14.5=py37h4d371b4_0
-  - chardet=4.0.0=py39h6e9494a_1
-  - cryptography=3.4.7=py38h1fa4640_0
-  - cycler=0.10.0=py_2
-  - dbus=1.13.6=ha13b53f_2
-  - decorator=5.0.6=pyhd8ed1ab_0
-  - defusedxml=0.7.1=pyhd8ed1ab_0
-  - entrypoints=0.3=pyhd8ed1ab_1003
-  - expat=2.3.0=he49afe7_0
-  - ffmpeg=4.3.1=hb787a4c_2
-  - fontconfig=2.13.1=hd23ceaa_1004
-  - freetype=2.10.4=h4cff582_1
-  - gast=0.4.0=pyh9f0ad1d_0
-  - gettext=0.19.8.1=h7937167_1005
-  - glib=2.68.1=he49afe7_0
-  - glib-tools=2.68.1=he49afe7_0
-  - gmp=6.2.1=h2e338ed_0
-  - gnutls=3.6.13=h756fd2b_1
-  - google-pasta=0.2.0=pyh8c360ce_0
-  - grpcio=1.37.0=py36h8d587b5_0
-  - gst-plugins-base=1.18.4=h63a84d5_1
-  - gstreamer=1.18.4=h8622b34_0
-  - h5py=2.10.0=nompi_py38h9a16e60_106
-  - hdf5=1.10.6=nompi_hc5d9132_1114
-  - icu=68.1=h74dc148_0
-  - idna=2.10=pyh9f0ad1d_0
-  - importlib-metadata=3.10.0=py39h6e9494a_0
-  - ipykernel=5.5.3=py38h6c79ece_0
-  - ipython=7.22.0=py38h6c79ece_0
-  - ipython_genutils=0.2.0=py_1
-  - ipywidgets=7.6.3=pyhd3deb0d_0
-  - jedi=0.18.0=py39h6e9494a_2
-  - jinja2=2.11.3=pyh44b312d_0
-  - joblib=1.0.1=pyhd8ed1ab_0
-  - jpeg=9d=hbcb3906_0
-  - jsonschema=3.2.0=pyhd8ed1ab_3
-  - jupyter=1.0.0=py39h6e9494a_6
-  - jupyter_client=6.1.12=pyhd8ed1ab_0
-  - jupyter_console=6.4.0=pyhd8ed1ab_0
-  - jupyter_core=4.7.1=py37hf985489_0
-  - jupyterlab_pygments=0.1.2=pyh9f0ad1d_0
-  - jupyterlab_widgets=1.0.0=pyhd8ed1ab_1
-  - keras-applications=1.0.8=py_1
-  - keras-preprocessing=1.1.2=pyhd8ed1ab_0
-  - kiwisolver=1.3.1=py36h615c93b_1
-  - krb5=1.17.2=h60d9502_0
-  - lame=3.100=h35c211d_1001
-  - lcms2=2.12=h577c468_0
-  - ld_impl_linux-64=2.35.1=h8edb8f9_2
-  - libblas=3.9.0=8_openblas
-  - libcblas=3.9.0=8_openblas
-  - libclang=11.1.0=default_he082bbe_0
-  - libcurl=7.76.0=h8ef9fac_0
-  - libedit=3.1.20191231=h0678c8f_2
-  - libev=4.33=haf1e3a3_1
-  - libevent=2.1.10=hddc9c9b_3
-  - libffi=3.3=h046ec9c_2
-  - libflac=1.3.3=h74dc148_1
-  - libgfortran5=9.3.0=h6c81a4c_17
-  - libglib=2.68.1=hd556434_0
-  - libiconv=1.16=haf1e3a3_0
-  - liblapack=3.9.0=8_openblas
-  - libllvm10=10.0.1=h009f743_3
-  - libllvm11=11.1.0=hd011deb_2
-  - libnghttp2=1.43.0=h07e645a_0
-  - libogg=1.3.4=h35c211d_1
-  - libopenblas=0.3.12=openmp_h63d9170_1
-  - libopus=1.3.1=hc929b4f_1
-  - libpng=1.6.37=h7cec526_2
-  - libpq=13.1=h052a64a_2
-  - libprotobuf=3.15.7=hcf210ce_0
-  - librosa=0.8.0=pyh9f0ad1d_0
-  - libsndfile=1.0.31=he49afe7_1
-  - libsodium=1.0.18=hbcb3906_1
-  - libssh2=1.9.0=h52ee1ee_6
-  - libtiff=4.2.0=h355d032_0
-  - libuuid=2.32.1=h35c211d_1000
-  - libvorbis=1.3.7=h046ec9c_0
-  - libwebp-base=1.2.0=h0d85af4_2
-  - libxcb=1.13=h35c211d_1003
-  - libxml2=2.9.10=h802ca4f_3
-  - llvmlite=0.36.0=py38h872f124_0
-  - lz4-c=1.9.3=h046ec9c_0
-  - markdown=3.3.4=pyhd8ed1ab_0
-  - markupsafe=1.1.1=py37hf967b71_3
-  - matplotlib-base=3.4.1=py39hb07454d_0
-  - mistune=0.8.4=py37hf967b71_1003
-  - mysql-common=8.0.23=h694c41f_1
-  - mysql-libs=8.0.23=h54f5a68_2
-  - nbclient=0.5.3=pyhd8ed1ab_0
-  - nbconvert=6.0.7=py38h50d1736_3
-  - nbformat=5.1.3=pyhd8ed1ab_0
-  - ncurses=6.2=h2e338ed_4
-  - nest-asyncio=1.5.1=pyhd8ed1ab_0
-  - nettle=3.6=hedd7734_0
-  - notebook=6.3.0=py37h5186d4c_0
-  - nspr=4.30=hcd9eead_0
-  - nss=3.63=h31e2bf1_0
-  - numba=0.53.1=py38h8fd2267_0
-  - numpy=1.20.2=py39h7eed0ac_0
-  - olefile=0.46=pyh9f0ad1d_1
-  - openh264=2.1.1=hfd3ada9_0
-  - openjpeg=2.4.0=h6cbf5cd_0
-  - openssl=1.1.1k=h0d85af4_0
-  - packaging=20.9=pyh44b312d_0
-  - pandas=1.2.3=py39h4d6be9b_0
-  - pandoc=2.12=h0d85af4_0
-  - pandocfilters=1.4.2=py36_0
-  - parso=0.8.2=pyhd8ed1ab_0
-  - pcre=8.44=h4a8c4bd_0
-  - pexpect=4.8.0=pyh9f0ad1d_2
-  - pickleshare=0.7.5=py_1003
-  - pillow=8.1.2=py38h83525de_1
-  - pip=21.0.1=pyhd8ed1ab_0
-  - pooch=1.3.0=pyhd8ed1ab_0
-  - prometheus_client=0.10.1=pyhd8ed1ab_0
-  - prompt-toolkit=3.0.18=pyha770c72_0
-  - prompt_toolkit=3.0.18=hd8ed1ab_0
-  - protobuf=3.15.7=py39h9fcab8e_0
-  - pthread-stubs=0.4=hc929b4f_1001
-  - ptyprocess=0.7.0=pyhd3deb0d_0
-  - pycparser=2.20=pyh9f0ad1d_2
-  - pygments=2.8.1=pyhd8ed1ab_0
-  - pyopenssl=20.0.1=pyhd8ed1ab_0
-  - pyparsing=2.4.7=pyh9f0ad1d_0
-  - pyqt=5.12.3=py38h50d1736_7
-  - pyqt-impl=5.12.3=py38h721a93c_7
-  - pyqt5-sip=4.19.18=py38h5745d40_7
-  - pyqtchart=5.12=py38h721a93c_7
-  - pyqtwebengine=5.12.1=py38h721a93c_7
-  - pyrsistent=0.17.3=py37hf967b71_2
-  - pysocks=1.7.1=py38h50d1736_3
-  - pysoundfile=0.10.3.post1=pyhd3deb0d_0
-  - python=3.7.10=h7728216_100_cpython
-  - python-dateutil=2.8.1=py_0
-  - python_abi=3.7=1_cp37m
-  - pytz=2021.1=pyhd8ed1ab_0
-  - pyzmq=22.0.3=py38hd3b92b6_1
-  - qt=5.12.9=h126340a_4
-  - qtconsole=5.0.3=pyhd8ed1ab_0
-  - qtpy=1.9.0=py_0
-  - readline=8.0=h0678c8f_2
-  - requests=2.25.1=pyhd3deb0d_0
-  - resampy=0.2.2=py_0
-  - scikit-learn=0.24.1=py38hfd19401_0
-  - scipy=1.6.2=py38h431c0a8_0
-  - send2trash=1.5.0=py_0
-  - setuptools=49.6.0=py38h50d1736_3
-  - six=1.15.0=pyh9f0ad1d_0
-  - sqlite=3.35.4=h44b9ce1_0
-  - tensorboard=1.14.0=py37_0
-  - tensorflow=1.14.0=h3cdfc77_0
-  - tensorflow-base=1.14.0=mkl_py37h5a24fda_0
-  - tensorflow-estimator=1.14.0=py37h5ca1d4c_0
-  - termcolor=1.1.0=py_2
-  - terminado=0.9.4=py37hf985489_0
-  - testpath=0.4.4=py_0
-  - threadpoolctl=2.1.0=pyh5ca1d4c_0
-  - tk=8.6.10=h0419947_1
-  - tornado=6.1=py37hf967b71_1
-  - traitlets=5.0.5=py_0
-  - typing_extensions=3.7.4.3=py_0
-  - urllib3=1.26.4=pyhd8ed1ab_0
-  - wcwidth=0.2.5=pyh9f0ad1d_2
-  - webencodings=0.5.1=py_1
-  - werkzeug=1.0.1=pyh9f0ad1d_0
-  - wheel=0.36.2=pyhd3deb0d_0
-  - widgetsnbextension=3.5.1=py37hf985489_4
-  - wrapt=1.12.1=py36h20b66c6_3
-  - x264=1!161.3030=h35c211d_0
-  - xorg-libxau=1.0.9=h35c211d_0
-  - xorg-libxdmcp=1.1.3=h35c211d_0
-  - xz=5.2.5=h0b31af3_1
-  - zeromq=4.3.4=h1c7c35f_0
-  - zipp=3.4.1=pyhd8ed1ab_0
-  - zlib=1.2.11=h7795811_1010
-  - zstd=1.4.9=h582d3a0_0
-  - pip:
-    - nvidia-cublas-cu11==11.10.3.66
-    - nvidia-cuda-nvrtc-cu11==11.7.99
-    - nvidia-cuda-runtime-cu11==11.7.99
-    - nvidia-cudnn-cu11==8.5.0.96
-    - torch==1.13.1
-prefix: /home/jacob/miniconda3/envs/species-id
diff --git a/conda_environments/environment_MacOS_BigSur.11.6.yml b/conda_environments/environment_MacOS_BigSur.11.6.yml
deleted file mode 100644
index 5d60eea..0000000
--- a/conda_environments/environment_MacOS_BigSur.11.6.yml
+++ /dev/null
@@ -1,377 +0,0 @@
-name: base
-channels:
-  - pytorch
-  - defaults
-dependencies:
-  - _anaconda_depends=2020.07=py38_0
-  - _ipyw_jlab_nb_ext_conf=0.1.0=py38_0
-  - alabaster=0.7.12=pyhd3eb1b0_0
-  - anaconda=custom=py38_1
-  - anaconda-clean=1.1.0=py38hecd8cb5_1
-  - anaconda-client=1.7.2=py38_0
-  - anaconda-navigator=2.1.4=py38hecd8cb5_0
-  - anaconda-project=0.9.1=pyhd3eb1b0_1
-  - anyio=2.2.0=py38hecd8cb5_1
-  - appdirs=1.4.4=py_0
-  - applaunchservices=0.2.1=py_0
-  - appnope=0.1.2=py38hecd8cb5_1001
-  - appscript=1.1.2=py38h9ed2024_0
-  - argh=0.26.2=py38_0
-  - argon2-cffi=20.1.0=py38h9ed2024_1
-  - asn1crypto=1.4.0=py_0
-  - astroid=2.5=py38hecd8cb5_1
-  - astropy=4.2.1=py38h9ed2024_1
-  - async_generator=1.10=pyhd3eb1b0_0
-  - atomicwrites=1.4.0=py_0
-  - attrs=20.3.0=pyhd3eb1b0_0
-  - autopep8=1.5.6=pyhd3eb1b0_0
-  - babel=2.9.0=pyhd3eb1b0_0
-  - backcall=0.2.0=pyhd3eb1b0_0
-  - backports=1.0=pyhd3eb1b0_2
-  - backports.functools_lru_cache=1.6.4=pyhd3eb1b0_0
-  - backports.shutil_get_terminal_size=1.0.0=pyhd3eb1b0_3
-  - backports.tempfile=1.0=pyhd3eb1b0_1
-  - backports.weakref=1.0.post1=py_1
-  - beautifulsoup4=4.9.3=pyha847dfd_0
-  - bitarray=1.9.2=py38h9ed2024_1
-  - bkcharts=0.2=py38_0
-  - black=19.10b0=py_0
-  - blas=1.0=mkl
-  - bleach=3.3.0=pyhd3eb1b0_0
-  - blosc=1.21.0=h2842e9f_0
-  - bokeh=2.3.2=py38hecd8cb5_0
-  - boto=2.49.0=py38_0
-  - bottleneck=1.3.2=py38hf1fa96c_1
-  - brotlipy=0.7.0=py38h9ed2024_1003
-  - bzip2=1.0.8=h1de35cc_0
-  - c-ares=1.17.1=h9ed2024_0
-  - ca-certificates=2022.4.26=hecd8cb5_0
-  - certifi=2021.10.8=py38hecd8cb5_2
-  - cffi=1.14.5=py38h2125817_0
-  - chardet=4.0.0=py38hecd8cb5_1003
-  - click=7.1.2=pyhd3eb1b0_0
-  - cloudpickle=1.6.0=py_0
-  - clyent=1.2.2=py38_1
-  - colorama=0.4.4=pyhd3eb1b0_0
-  - conda=4.12.0=py38hecd8cb5_0
-  - conda-build=3.21.4=py38hecd8cb5_0
-  - conda-content-trust=0.1.1=pyhd3eb1b0_0
-  - conda-env=2.6.0=1
-  - conda-package-handling=1.7.3=py38h9ed2024_1
-  - conda-repo-cli=1.0.4=pyhd3eb1b0_0
-  - conda-token=0.3.0=pyhd3eb1b0_0
-  - conda-verify=3.4.2=py_1
-  - contextlib2=0.6.0.post1=py_0
-  - cryptography=3.4.7=py38h2fd3fbb_0
-  - curl=7.71.1=hb0a8c7a_1
-  - cycler=0.10.0=py38_0
-  - cython=0.29.23=py38h23ab428_0
-  - cytoolz=0.11.0=py38haf1e3a3_0
-  - dask=2021.4.0=pyhd3eb1b0_0
-  - dask-core=2021.4.0=pyhd3eb1b0_0
-  - dbus=1.13.18=h18a8e69_0
-  - decorator=5.0.6=pyhd3eb1b0_0
-  - defusedxml=0.7.1=pyhd3eb1b0_0
-  - diff-match-patch=20200713=py_0
-  - distributed=2021.4.0=py38hecd8cb5_0
-  - docutils=0.17=py38hecd8cb5_1
-  - entrypoints=0.3=py38_0
-  - et_xmlfile=1.0.1=py_1001
-  - expat=2.3.0=h23ab428_2
-  - fastcache=1.1.0=py38h1de35cc_0
-  - ffmpeg=4.3=h0a44026_0
-  - filelock=3.0.12=pyhd3eb1b0_1
-  - flake8=3.9.0=pyhd3eb1b0_0
-  - flask=1.1.2=pyhd3eb1b0_0
-  - freetype=2.10.4=ha233b18_0
-  - fsspec=0.9.0=pyhd3eb1b0_0
-  - future=0.18.2=py38_1
-  - get_terminal_size=1.0.0=h7520d66_0
-  - gettext=0.21.0=h7535e17_0
-  - gevent=21.1.2=py38h9ed2024_1
-  - glib=2.68.1=hdf23fa2_0
-  - glob2=0.7=pyhd3eb1b0_0
-  - gmp=6.2.1=h23ab428_2
-  - gmpy2=2.0.8=py38h6ef4df4_3
-  - gnutls=3.6.15=hed9c0bf_0
-  - greenlet=1.0.0=py38h23ab428_2
-  - h5py=2.10.0=py38h3134771_0
-  - hdf5=1.10.4=hfa1e0ec_0
-  - heapdict=1.0.1=py_0
-  - html5lib=1.1=py_0
-  - icu=58.2=h0a44026_3
-  - idna=2.10=pyhd3eb1b0_0
-  - imageio=2.9.0=pyhd3eb1b0_0
-  - imagesize=1.2.0=pyhd3eb1b0_0
-  - importlib-metadata=3.10.0=py38hecd8cb5_0
-  - importlib_metadata=3.10.0=hd3eb1b0_0
-  - iniconfig=1.1.1=pyhd3eb1b0_0
-  - intel-openmp=2021.2.0=hecd8cb5_564
-  - intervaltree=3.1.0=py_0
-  - ipykernel=5.3.4=py38h5ca1d4c_0
-  - ipython=7.22.0=py38h01d92e1_0
-  - ipython_genutils=0.2.0=pyhd3eb1b0_1
-  - ipywidgets=7.6.3=pyhd3eb1b0_1
-  - isort=5.8.0=pyhd3eb1b0_0
-  - itsdangerous=1.1.0=pyhd3eb1b0_0
-  - jbig=2.1=h4d881f8_0
-  - jdcal=1.4.1=py_0
-  - jedi=0.17.2=py38hecd8cb5_1
-  - jinja2=2.11.3=pyhd3eb1b0_0
-  - joblib=1.0.1=pyhd3eb1b0_0
-  - jpeg=9b=he5867d9_2
-  - json5=0.9.5=py_0
-  - jsonschema=3.2.0=py_2
-  - jupyter=1.0.0=py38_7
-  - jupyter-packaging=0.7.12=pyhd3eb1b0_0
-  - jupyter_client=6.1.12=pyhd3eb1b0_0
-  - jupyter_console=6.4.0=pyhd3eb1b0_0
-  - jupyter_core=4.7.1=py38hecd8cb5_0
-  - jupyter_server=1.4.1=py38hecd8cb5_0
-  - jupyterlab=3.0.14=pyhd3eb1b0_1
-  - jupyterlab_pygments=0.1.2=py_0
-  - jupyterlab_server=2.4.0=pyhd3eb1b0_0
-  - jupyterlab_widgets=1.0.0=pyhd3eb1b0_1
-  - keyring=22.3.0=py38hecd8cb5_0
-  - kiwisolver=1.3.1=py38h23ab428_0
-  - krb5=1.18.2=h75d18d8_0
-  - lame=3.100=h1de35cc_0
-  - lazy-object-proxy=1.6.0=py38h9ed2024_0
-  - lcms2=2.12=hf1fd2bf_0
-  - libarchive=3.4.2=haa3ed63_0
-  - libcurl=7.71.1=h8a08a2b_1
-  - libcxx=10.0.0=1
-  - libedit=3.1.20210216=h9ed2024_1
-  - libev=4.33=haf1e3a3_0
-  - libffi=3.3=hb1e8313_2
-  - libgfortran=3.0.1=h93005f0_2
-  - libiconv=1.16=h1de35cc_0
-  - libidn2=2.3.1=h9ed2024_0
-  - liblief=0.10.1=h0a44026_0
-  - libllvm10=10.0.1=h76017ad_5
-  - libllvm9=9.0.1=h21ff451_1
-  - libpng=1.6.37=ha441bb4_0
-  - libsodium=1.0.18=h1de35cc_0
-  - libspatialindex=1.9.3=h23ab428_0
-  - libssh2=1.9.0=ha12b0ac_1
-  - libtasn1=4.16.0=h9ed2024_0
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-  - libunistring=0.9.10=h9ed2024_0
-  - libuv=1.40.0=haf1e3a3_0
-  - libwebp-base=1.2.0=h9ed2024_0
-  - libxml2=2.9.10=h7cdb67c_3
-  - libxslt=1.1.34=h83b36ba_0
-  - llvm-openmp=10.0.0=h28b9765_0
-  - llvmlite=0.36.0=py38he4411ff_4
-  - locket=0.2.1=py38hecd8cb5_1
-  - lxml=4.6.3=py38h26b266a_0
-  - lz4-c=1.9.3=h23ab428_0
-  - lzo=2.10=haf1e3a3_2
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-  - matplotlib=3.3.4=py38hecd8cb5_0
-  - matplotlib-base=3.3.4=py38h8b3ea08_0
-  - mccabe=0.6.1=py38_1
-  - mistune=0.8.4=py38h1de35cc_1001
-  - mkl=2021.2.0=hecd8cb5_269
-  - mkl-service=2.3.0=py38h9ed2024_1
-  - mkl_fft=1.3.0=py38h4a7008c_2
-  - mkl_random=1.2.1=py38hb2f4e1b_2
-  - mock=4.0.3=pyhd3eb1b0_0
-  - more-itertools=8.7.0=pyhd3eb1b0_0
-  - mpc=1.1.0=h6ef4df4_1
-  - mpfr=4.0.2=h9066e36_1
-  - mpmath=1.2.1=py38hecd8cb5_0
-  - msgpack-python=1.0.2=py38hf7b0b51_1
-  - multipledispatch=0.6.0=py38_0
-  - mypy_extensions=0.4.3=py38_0
-  - navigator-updater=0.2.1=py38_0
-  - nbclassic=0.2.6=pyhd3eb1b0_0
-  - nbclient=0.5.3=pyhd3eb1b0_0
-  - nbconvert=6.0.7=py38_0
-  - nbformat=5.1.3=pyhd3eb1b0_0
-  - ncurses=6.2=h0a44026_1
-  - nest-asyncio=1.5.1=pyhd3eb1b0_0
-  - nettle=3.7.3=h230ac6f_1
-  - networkx=2.5=py_0
-  - ninja=1.10.2=hf7b0b51_1
-  - nltk=3.6.1=pyhd3eb1b0_0
-  - nose=1.3.7=pyhd3eb1b0_1006
-  - notebook=6.3.0=py38hecd8cb5_0
-  - numba=0.53.1=py38hb2f4e1b_0
-  - numexpr=2.7.3=py38h5873af2_1
-  - numpy-base=1.20.1=py38h585ceec_0
-  - numpydoc=1.1.0=pyhd3eb1b0_1
-  - olefile=0.46=py_0
-  - openh264=2.1.0=hd9629dc_0
-  - openpyxl=3.0.7=pyhd3eb1b0_0
-  - openssl=1.1.1n=hca72f7f_0
-  - packaging=20.9=pyhd3eb1b0_0
-  - pandas=1.2.4=py38h23ab428_0
-  - pandoc=2.12=hecd8cb5_0
-  - pandocfilters=1.4.3=py38hecd8cb5_1
-  - parso=0.7.0=py_0
-  - partd=1.2.0=pyhd3eb1b0_0
-  - path=15.1.2=py38hecd8cb5_0
-  - path.py=12.5.0=0
-  - pathlib2=2.3.5=py38hecd8cb5_2
-  - pathspec=0.7.0=py_0
-  - pathtools=0.1.2=pyhd3eb1b0_1
-  - patsy=0.5.1=py38_0
-  - pcre=8.44=hb1e8313_0
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-  - pexpect=4.8.0=pyhd3eb1b0_3
-  - pickleshare=0.7.5=pyhd3eb1b0_1003
-  - pillow=8.2.0=py38h5270095_0
-  - pip=21.0.1=py38hecd8cb5_0
-  - pkginfo=1.7.0=py38hecd8cb5_0
-  - pluggy=0.13.1=py38hecd8cb5_0
-  - ply=3.11=py38_0
-  - prometheus_client=0.10.1=pyhd3eb1b0_0
-  - prompt-toolkit=3.0.17=pyh06a4308_0
-  - prompt_toolkit=3.0.17=hd3eb1b0_0
-  - psutil=5.8.0=py38h9ed2024_1
-  - ptyprocess=0.7.0=pyhd3eb1b0_2
-  - py=1.10.0=pyhd3eb1b0_0
-  - py-lief=0.10.1=py38haf313ee_0
-  - pycodestyle=2.6.0=pyhd3eb1b0_0
-  - pycosat=0.6.3=py38h1de35cc_1
-  - pycparser=2.20=py_2
-  - pycurl=7.43.0.6=py38hddc9c9b_0
-  - pydocstyle=6.0.0=pyhd3eb1b0_0
-  - pyerfa=1.7.3=py38h9ed2024_0
-  - pyflakes=2.2.0=pyhd3eb1b0_0
-  - pygments=2.8.1=pyhd3eb1b0_0
-  - pyjwt=2.1.0=py38hecd8cb5_0
-  - pylint=2.7.4=py38hecd8cb5_1
-  - pyls-black=0.4.6=hd3eb1b0_0
-  - pyls-spyder=0.3.2=pyhd3eb1b0_0
-  - pyodbc=4.0.30=py38h0a44026_0
-  - pyopenssl=20.0.1=pyhd3eb1b0_1
-  - pyparsing=2.4.7=pyhd3eb1b0_0
-  - pyqt=5.9.2=py38h655552a_2
-  - pyrsistent=0.17.3=py38haf1e3a3_0
-  - pysocks=1.7.1=py38_1
-  - pytables=3.6.1=py38h4727e94_0
-  - pytest=6.2.3=py38hecd8cb5_2
-  - python=3.8.8=h88f2d9e_5
-  - python-dateutil=2.8.1=pyhd3eb1b0_0
-  - python-jsonrpc-server=0.4.0=py_0
-  - python-language-server=0.36.2=pyhd3eb1b0_0
-  - python-libarchive-c=2.9=pyhd3eb1b0_1
-  - python.app=3=py38h9ed2024_0
-  - pytorch=1.9.0=py3.8_0
-  - pytz=2021.1=pyhd3eb1b0_0
-  - pywavelets=1.1.1=py38haf1e3a3_2
-  - pyyaml=5.4.1=py38h9ed2024_1
-  - pyzmq=20.0.0=py38h23ab428_1
-  - qdarkstyle=2.8.1=py_0
-  - qt=5.9.7=h468cd18_1
-  - qtawesome=1.0.2=pyhd3eb1b0_0
-  - qtconsole=5.0.3=pyhd3eb1b0_0
-  - qtpy=1.9.0=py_0
-  - readline=8.1=h9ed2024_0
-  - regex=2021.4.4=py38h9ed2024_0
-  - requests=2.25.1=pyhd3eb1b0_0
-  - ripgrep=12.1.1=0
-  - rope=0.18.0=py_0
-  - rtree=0.9.7=py38hecd8cb5_1
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-  - scikit-image=0.18.1=py38hb2f4e1b_0
-  - scikit-learn=0.24.1=py38hb2f4e1b_0
-  - scipy=1.6.2=py38hd5f7400_1
-  - seaborn=0.11.1=pyhd3eb1b0_0
-  - send2trash=1.5.0=pyhd3eb1b0_1
-  - setuptools=52.0.0=py38hecd8cb5_0
-  - simplegeneric=0.8.1=py38_2
-  - singledispatch=3.6.1=pyhd3eb1b0_1001
-  - sip=4.19.8=py38h0a44026_0
-  - six=1.15.0=py38hecd8cb5_0
-  - snappy=1.1.8=hb1e8313_0
-  - sniffio=1.2.0=py38hecd8cb5_1
-  - snowballstemmer=2.1.0=pyhd3eb1b0_0
-  - sortedcollections=2.1.0=pyhd3eb1b0_0
-  - sortedcontainers=2.3.0=pyhd3eb1b0_0
-  - soupsieve=2.2.1=pyhd3eb1b0_0
-  - sphinx=4.0.1=pyhd3eb1b0_0
-  - sphinxcontrib=1.0=py38_1
-  - sphinxcontrib-applehelp=1.0.2=pyhd3eb1b0_0
-  - sphinxcontrib-devhelp=1.0.2=pyhd3eb1b0_0
-  - sphinxcontrib-htmlhelp=1.0.3=pyhd3eb1b0_0
-  - sphinxcontrib-jsmath=1.0.1=pyhd3eb1b0_0
-  - sphinxcontrib-qthelp=1.0.3=pyhd3eb1b0_0
-  - sphinxcontrib-serializinghtml=1.1.4=pyhd3eb1b0_0
-  - sphinxcontrib-websupport=1.2.4=py_0
-  - spyder=4.2.5=py38hecd8cb5_0
-  - spyder-kernels=1.10.2=py38hecd8cb5_0
-  - sqlalchemy=1.4.7=py38h9ed2024_0
-  - sqlite=3.35.4=hce871da_0
-  - statsmodels=0.12.2=py38h9ed2024_0
-  - sympy=1.8=py38hecd8cb5_0
-  - tbb=2020.3=h879752b_0
-  - tblib=1.7.0=py_0
-  - terminado=0.9.4=py38hecd8cb5_0
-  - testpath=0.4.4=pyhd3eb1b0_0
-  - textdistance=4.2.1=pyhd3eb1b0_0
-  - threadpoolctl=2.1.0=pyh5ca1d4c_0
-  - three-merge=0.1.1=pyhd3eb1b0_0
-  - tifffile=2020.10.1=py38h0cf3a3e_2
-  - tk=8.6.10=hb0a8c7a_0
-  - toml=0.10.2=pyhd3eb1b0_0
-  - toolz=0.11.1=pyhd3eb1b0_0
-  - torchaudio=0.9.0=py38
-  - torchvision=0.10.0=py38_cpu
-  - tornado=6.1=py38h9ed2024_0
-  - tqdm=4.59.0=pyhd3eb1b0_1
-  - traitlets=5.0.5=pyhd3eb1b0_0
-  - typed-ast=1.4.2=py38h9ed2024_1
-  - typing_extensions=4.1.1=pyh06a4308_0
-  - ujson=4.0.2=py38h23ab428_0
-  - unicodecsv=0.14.1=py38_0
-  - unixodbc=2.3.9=haf1e3a3_0
-  - urllib3=1.26.4=pyhd3eb1b0_0
-  - watchdog=1.0.2=py38h9ed2024_1
-  - wcwidth=0.2.5=py_0
-  - webencodings=0.5.1=py38_1
-  - werkzeug=1.0.1=pyhd3eb1b0_0
-  - wheel=0.36.2=pyhd3eb1b0_0
-  - widgetsnbextension=3.5.1=py38_0
-  - wrapt=1.12.1=py38haf1e3a3_1
-  - wurlitzer=2.1.0=py38hecd8cb5_0
-  - xlrd=2.0.1=pyhd3eb1b0_0
-  - xlsxwriter=1.3.8=pyhd3eb1b0_0
-  - xlwings=0.23.0=py38hecd8cb5_0
-  - xlwt=1.3.0=py38_0
-  - xmltodict=0.12.0=py_0
-  - xz=5.2.5=h1de35cc_0
-  - yaml=0.2.5=haf1e3a3_0
-  - yapf=0.31.0=pyhd3eb1b0_0
-  - zeromq=4.3.4=h23ab428_0
-  - zict=2.0.0=pyhd3eb1b0_0
-  - zipp=3.4.1=pyhd3eb1b0_0
-  - zlib=1.2.11=h1de35cc_3
-  - zope=1.0=py38_1
-  - zope.event=4.5.0=py38_0
-  - zope.interface=5.3.0=py38h9ed2024_0
-  - zstd=1.4.5=h41d2c2f_0
-  - pip:
-    - absl-py==1.0.0
-    - aws-lambda-typing==2.9.2
-    - backend==0.2.4.1
-    - boto3==1.20.23
-    - boto3-stubs==1.21.0
-    - botocore==1.23.54
-    - botocore-stubs==1.24.0
-    - flask-jwt-extended==4.2.3
-    - jmespath==0.10.0
-    - mediapipe==0.8.8.1
-    - numpy==1.21.2
-    - nvidia-cublas-cu11==11.10.3.66
-    - nvidia-cuda-nvrtc-cu11==11.7.99
-    - nvidia-cuda-runtime-cu11==11.7.99
-    - nvidia-cudnn-cu11==8.5.0.96
-    - opencv-contrib-python==4.5.5.62
-    - protobuf==3.19.4
-    - s3transfer==0.5.1
-    - torch==1.13.1
-    - typing-extensions==3.10.0.2
-prefix: /Users/mugetronblue/opt/anaconda3
diff --git a/conda_environments/environment_Ubuntu16.04.yaml b/conda_environments/environment_Ubuntu16.04.yaml
deleted file mode 100644
index 8d69d3a..0000000
--- a/conda_environments/environment_Ubuntu16.04.yaml
+++ /dev/null
@@ -1,205 +0,0 @@
-name: species-id
-channels:
-  - conda-forge
-  - defaults
-dependencies:
-  - _libgcc_mutex=0.1=main
-  - _tflow_select=2.3.0=eigen
-  - absl-py=0.11.0=py38h578d9bd_0
-  - aiohttp=3.7.3=py38h25fe258_0
-  - appdirs=1.4.3=py_0
-  - argon2-cffi=20.1.0=py38h25fe258_2
-  - astor=0.8.1=pyh9f0ad1d_0
-  - astunparse=1.6.3=pyhd8ed1ab_0
-  - async-timeout=3.0.1=py_1000
-  - async_generator=1.10=py_0
-  - attrs=20.3.0=pyhd3deb0d_0
-  - audioread=2.1.8=py38h32f6830_2
-  - backcall=0.2.0=pyh9f0ad1d_0
-  - backports=1.0=py_2
-  - backports.functools_lru_cache=1.6.1=py_0
-  - blas=1.0=mkl
-  - bleach=3.2.2=pyh44b312d_0
-  - blinker=1.4=py_1
-  - brotlipy=0.7.0=py38h7b6447c_1000
-  - bzip2=1.0.8=h7b6447c_0
-  - c-ares=1.17.1=h36c2ea0_0
-  - ca-certificates=2020.12.5=ha878542_0
-  - cachetools=4.2.1=pyhd8ed1ab_0
-  - certifi=2020.12.5=py38h578d9bd_1
-  - cffi=1.14.0=py38he30daa8_1
-  - chardet=3.0.4=py38_1003
-  - click=7.1.2=pyh9f0ad1d_0
-  - cryptography=2.9.2=py38h1ba5d50_0
-  - cycler=0.10.0=py38_0
-  - dbus=1.13.16=hb2f20db_0
-  - decorator=4.4.2=py_0
-  - defusedxml=0.6.0=py_0
-  - entrypoints=0.3=pyhd8ed1ab_1003
-  - expat=2.2.9=he6710b0_2
-  - ffmpeg=4.2.2=h20bf706_0
-  - fontconfig=2.13.0=h9420a91_0
-  - freetype=2.10.2=h5ab3b9f_0
-  - gast=0.3.3=py_0
-  - gettext=0.19.8.1=h9b4dc7a_1
-  - glib=2.65.0=h3eb4bd4_0
-  - gmp=6.1.2=h6c8ec71_1
-  - gnutls=3.6.5=h71b1129_1002
-  - google-auth=1.24.0=pyhd3deb0d_0
-  - google-auth-oauthlib=0.4.1=py_2
-  - google-pasta=0.2.0=pyh8c360ce_0
-  - grpcio=1.33.2=py38heead2fc_2
-  - gst-plugins-base=1.14.0=hbbd80ab_1
-  - gstreamer=1.14.0=hb31296c_0
-  - h5py=2.10.0=nompi_py38h7442b35_105
-  - hdf5=1.10.6=nompi_h3c11f04_101
-  - icu=58.2=he6710b0_3
-  - idna=2.10=py_0
-  - importlib-metadata=3.4.0=py38h578d9bd_0
-  - importlib_metadata=3.4.0=hd8ed1ab_0
-  - intel-openmp=2020.1=217
-  - ipykernel=5.4.3=py38h81c977d_0
-  - ipython=7.12.0=py38h5ca1d4c_0
-  - ipython_genutils=0.2.0=py_1
-  - ipywidgets=7.6.3=pyhd3deb0d_0
-  - jedi=0.18.0=py38h578d9bd_2
-  - jinja2=2.11.2=pyh9f0ad1d_0
-  - joblib=0.16.0=py_0
-  - jpeg=9b=h024ee3a_2
-  - jsonschema=3.2.0=py_2
-  - jupyter=1.0.0=py38h578d9bd_4
-  - jupyter_client=6.1.11=pyhd8ed1ab_1
-  - jupyter_console=6.2.0=py_0
-  - jupyter_core=4.7.0=py38h578d9bd_1
-  - jupyterlab_pygments=0.1.2=pyh9f0ad1d_0
-  - jupyterlab_widgets=1.0.0=pyhd8ed1ab_1
-  - keras-preprocessing=1.1.2=pyhd8ed1ab_0
-  - kiwisolver=1.2.0=py38hfd86e86_0
-  - lame=3.100=h7b6447c_0
-  - ld_impl_linux-64=2.33.1=h53a641e_7
-  - libedit=3.1.20191231=h14c3975_1
-  - libffi=3.3=he6710b0_2
-  - libflac=1.3.3=he1b5a44_0
-  - libgcc-ng=9.1.0=hdf63c60_0
-  - libgfortran-ng=7.3.0=hdf63c60_0
-  - libllvm9=9.0.1=h4a3c616_1
-  - libogg=1.3.2=h7b6447c_0
-  - libopus=1.3.1=h7b6447c_0
-  - libpng=1.6.37=hbc83047_0
-  - libprotobuf=3.13.0.1=h8b12597_0
-  - librosa=0.8.0=pyh9f0ad1d_0
-  - libsndfile=1.0.28=he1b5a44_1000
-  - libsodium=1.0.18=h36c2ea0_1
-  - libstdcxx-ng=9.1.0=hdf63c60_0
-  - libuuid=1.0.3=h1bed415_2
-  - libvorbis=1.3.6=h7b6447c_0
-  - libvpx=1.7.0=h439df22_0
-  - libxcb=1.14=h7b6447c_0
-  - libxml2=2.9.10=he19cac6_1
-  - llvmlite=0.33.0=py38hc6ec683_1
-  - mad=0.15.1b=he1b5a44_0
-  - markdown=3.3.3=pyh9f0ad1d_0
-  - markupsafe=1.1.1=py38h8df0ef7_2
-  - matplotlib=3.2.2=0
-  - matplotlib-base=3.2.2=py38hef1b27d_0
-  - mistune=0.8.4=py38h25fe258_1002
-  - mkl=2020.1=217
-  - mkl-service=2.3.0=py38he904b0f_0
-  - mkl_fft=1.1.0=py38h23d657b_0
-  - mkl_random=1.1.1=py38h0573a6f_0
-  - multidict=4.7.5=py38h1e0a361_2
-  - nbclient=0.5.1=py_0
-  - nbconvert=6.0.7=py38h578d9bd_3
-  - nbformat=5.1.2=pyhd8ed1ab_1
-  - ncurses=6.2=he6710b0_1
-  - nest-asyncio=1.4.3=pyhd8ed1ab_0
-  - nettle=3.4.1=hbb512f6_0
-  - notebook=6.2.0=py38h06a4308_0
-  - numba=0.50.1=py38h0573a6f_1
-  - oauthlib=3.0.1=py_0
-  - openh264=2.1.0=hd408876_0
-  - openssl=1.1.1h=h516909a_0
-  - packaging=20.4=py_0
-  - pandas=1.1.4=py38h0ef3d22_0
-  - pandoc=2.11.4=h7f98852_0
-  - pandocfilters=1.4.2=py_1
-  - parso=0.8.1=pyhd8ed1ab_0
-  - pcre=8.44=he6710b0_0
-  - pexpect=4.8.0=pyh9f0ad1d_2
-  - pickleshare=0.7.5=py_1003
-  - pip=20.1.1=py38_1
-  - pooch=1.1.1=py_0
-  - prometheus_client=0.9.0=pyhd3deb0d_0
-  - prompt-toolkit=3.0.14=pyha770c72_0
-  - prompt_toolkit=3.0.14=hd8ed1ab_0
-  - protobuf=3.13.0.1=py38hadf7658_1
-  - ptyprocess=0.7.0=pyhd3deb0d_0
-  - pyasn1=0.4.8=py_0
-  - pyasn1-modules=0.2.7=py_0
-  - pycparser=2.20=py_2
-  - pygments=2.7.4=pyhd8ed1ab_0
-  - pyjwt=2.0.1=pyhd8ed1ab_0
-  - pyopenssl=19.1.0=py_1
-  - pyparsing=2.4.7=py_0
-  - pyqt=5.9.2=py38h05f1152_4
-  - pyrsistent=0.17.3=py38h25fe258_1
-  - pysocks=1.7.1=py38_0
-  - pysoundfile=0.10.2=py_1001
-  - python=3.8.5=hcff3b4d_0
-  - python-dateutil=2.8.1=py_0
-  - python_abi=3.8=1_cp38
-  - pytz=2020.5=pyhd8ed1ab_0
-  - pyzmq=20.0.0=py38h1d1b12f_1
-  - qt=5.9.7=h5867ecd_1
-  - qtconsole=5.0.2=pyhd8ed1ab_0
-  - qtpy=1.9.0=py_0
-  - readline=8.0=h7b6447c_0
-  - requests=2.24.0=py_0
-  - requests-oauthlib=1.3.0=pyh9f0ad1d_0
-  - resampy=0.2.2=py_0
-  - rsa=4.7=pyhd3deb0d_0
-  - scikit-learn=0.23.1=py38h423224d_0
-  - send2trash=1.5.0=py_0
-  - setuptools=49.2.0=py38_0
-  - sip=4.19.13=py38he6710b0_0
-  - six=1.15.0=py_0
-  - sox=14.4.2=h27f72bc_1013
-  - sqlite=3.32.3=h62c20be_0
-  - tbb=2020.0=hfd86e86_0
-  - tensorboard=2.4.1=pyhd8ed1ab_0
-  - tensorboard-plugin-wit=1.8.0=pyh44b312d_0
-  - tensorflow=2.3.0=eigen_py38h71ff20e_0
-  - tensorflow-base=2.3.0=eigen_py38hb57a387_0
-  - termcolor=1.1.0=py_2
-  - terminado=0.9.2=py38h578d9bd_0
-  - testpath=0.4.4=py_0
-  - threadpoolctl=2.1.0=pyh5ca1d4c_0
-  - tk=8.6.10=hbc83047_0
-  - tornado=6.0.4=py38h7b6447c_1
-  - traitlets=5.0.5=py_0
-  - typing-extensions=3.7.4.3=0
-  - typing_extensions=3.7.4.3=py_0
-  - urllib3=1.25.9=py_0
-  - wcwidth=0.2.5=pyh9f0ad1d_2
-  - webencodings=0.5.1=py_1
-  - werkzeug=1.0.1=pyh9f0ad1d_0
-  - wheel=0.34.2=py38_0
-  - widgetsnbextension=3.5.1=py38h578d9bd_4
-  - wrapt=1.12.1=py38h25fe258_2
-  - x264=1!157.20191217=h7b6447c_0
-  - xz=5.2.5=h7b6447c_0
-  - yarl=1.6.3=py38h25fe258_0
-  - zeromq=4.3.3=h58526e2_3
-  - zipp=3.4.0=py_0
-  - zlib=1.2.11=h7b6447c_3
-  - pip:
-    - numpy==1.18.5
-    - nvidia-cublas-cu11==11.10.3.66
-    - nvidia-cuda-nvrtc-cu11==11.7.99
-    - nvidia-cuda-runtime-cu11==11.7.99
-    - nvidia-cudnn-cu11==8.5.0.96
-    - opt-einsum==3.3.0
-    - scipy==1.4.1
-    - tensorflow-estimator==2.3.0
-    - torch==1.13.1
-prefix: /home/jacob/anaconda3/envs/species-id
diff --git a/conda_environments/environment_Ubuntu18.04.yml b/conda_environments/environment_Ubuntu18.04.yml
deleted file mode 100644
index 43aec96..0000000
--- a/conda_environments/environment_Ubuntu18.04.yml
+++ /dev/null
@@ -1,215 +0,0 @@
-name: species-id
-channels:
-  - conda-forge
-  - defaults
-dependencies:
-  - _libgcc_mutex=0.1=conda_forge
-  - _openmp_mutex=4.5=1_gnu
-  - absl-py=0.12.0=pyhd8ed1ab_0
-  - appdirs=1.4.4=pyh9f0ad1d_0
-  - argon2-cffi=20.1.0=py37h5e8e339_2
-  - astor=0.8.1=pyh9f0ad1d_0
-  - async_generator=1.10=py_0
-  - attrs=20.3.0=pyhd3deb0d_0
-  - audioread=2.1.9=py37h89c1867_0
-  - backcall=0.2.0=pyh9f0ad1d_0
-  - backports=1.0=py_2
-  - backports.functools_lru_cache=1.6.3=pyhd8ed1ab_0
-  - bleach=3.3.0=pyh44b312d_0
-  - brotlipy=0.7.0=py37h5e8e339_1001
-  - bzip2=1.0.8=h7f98852_4
-  - c-ares=1.17.1=h7f98852_1
-  - ca-certificates=2020.12.5=ha878542_0
-  - cached-property=1.5.2=hd8ed1ab_1
-  - cached_property=1.5.2=pyha770c72_1
-  - certifi=2020.12.5=py37h89c1867_1
-  - cffi=1.14.5=py37hc58025e_0
-  - chardet=4.0.0=py37h89c1867_1
-  - cryptography=3.4.7=py37h5d9358c_0
-  - cycler=0.10.0=py_2
-  - dbus=1.13.6=h48d8840_2
-  - decorator=5.0.6=pyhd8ed1ab_0
-  - defusedxml=0.7.1=pyhd8ed1ab_0
-  - entrypoints=0.3=pyhd8ed1ab_1003
-  - expat=2.3.0=h9c3ff4c_0
-  - ffmpeg=4.3.1=hca11adc_2
-  - fontconfig=2.13.1=hba837de_1004
-  - freetype=2.10.4=h0708190_1
-  - gast=0.4.0=pyh9f0ad1d_0
-  - gettext=0.19.8.1=h0b5b191_1005
-  - glib=2.68.1=h9c3ff4c_0
-  - glib-tools=2.68.1=h9c3ff4c_0
-  - gmp=6.2.1=h58526e2_0
-  - gnutls=3.6.13=h85f3911_1
-  - google-pasta=0.2.0=pyh8c360ce_0
-  - grpcio=1.37.0=py37hb27c1af_0
-  - gst-plugins-base=1.18.4=h29181c9_0
-  - gstreamer=1.18.4=h76c114f_0
-  - h5py=2.10.0=nompi_py37ha3df211_106
-  - hdf5=1.10.6=nompi_h6a2412b_1114
-  - icu=68.1=h58526e2_0
-  - idna=2.10=pyh9f0ad1d_0
-  - importlib-metadata=3.10.0=py37h89c1867_0
-  - ipykernel=5.5.3=py37h085eea5_0
-  - ipython=7.22.0=py37h085eea5_0
-  - ipython_genutils=0.2.0=py_1
-  - ipywidgets=7.6.3=pyhd3deb0d_0
-  - jedi=0.18.0=py37h89c1867_2
-  - jinja2=2.11.3=pyh44b312d_0
-  - joblib=1.0.1=pyhd8ed1ab_0
-  - jpeg=9d=h36c2ea0_0
-  - jsonschema=3.2.0=pyhd8ed1ab_3
-  - jupyter=1.0.0=py37h89c1867_6
-  - jupyter_client=6.1.12=pyhd8ed1ab_0
-  - jupyter_console=6.4.0=pyhd8ed1ab_0
-  - jupyter_core=4.7.1=py37h89c1867_0
-  - jupyterlab_pygments=0.1.2=pyh9f0ad1d_0
-  - jupyterlab_widgets=1.0.0=pyhd8ed1ab_1
-  - keras-applications=1.0.8=py_1
-  - keras-preprocessing=1.1.2=pyhd8ed1ab_0
-  - kiwisolver=1.3.1=py37h2527ec5_1
-  - krb5=1.17.2=h926e7f8_0
-  - lame=3.100=h7f98852_1001
-  - lcms2=2.12=hddcbb42_0
-  - ld_impl_linux-64=2.35.1=hea4e1c9_2
-  - libblas=3.9.0=8_openblas
-  - libcblas=3.9.0=8_openblas
-  - libclang=11.1.0=default_ha53f305_0
-  - libcurl=7.76.0=hc4aaa36_0
-  - libedit=3.1.20191231=he28a2e2_2
-  - libev=4.33=h516909a_1
-  - libevent=2.1.10=hcdb4288_3
-  - libffi=3.3=h58526e2_2
-  - libflac=1.3.3=h9c3ff4c_1
-  - libgcc-ng=9.3.0=h2828fa1_18
-  - libgfortran-ng=9.3.0=hff62375_18
-  - libgfortran5=9.3.0=hff62375_18
-  - libglib=2.68.1=h3e27bee_0
-  - libgomp=9.3.0=h2828fa1_18
-  - libiconv=1.16=h516909a_0
-  - liblapack=3.9.0=8_openblas
-  - libllvm10=10.0.1=he513fc3_3
-  - libllvm11=11.1.0=hf817b99_2
-  - libnghttp2=1.43.0=h812cca2_0
-  - libogg=1.3.4=h7f98852_1
-  - libopenblas=0.3.12=pthreads_h4812303_1
-  - libopus=1.3.1=h7f98852_1
-  - libpng=1.6.37=h21135ba_2
-  - libpq=13.1=hfd2b0eb_2
-  - libprotobuf=3.15.7=h780b84a_0
-  - librosa=0.8.0=pyh9f0ad1d_0
-  - libsndfile=1.0.31=h9c3ff4c_1
-  - libsodium=1.0.18=h36c2ea0_1
-  - libssh2=1.9.0=ha56f1ee_6
-  - libstdcxx-ng=9.3.0=h6de172a_18
-  - libtiff=4.2.0=hdc55705_0
-  - libuuid=2.32.1=h7f98852_1000
-  - libvorbis=1.3.7=h9c3ff4c_0
-  - libwebp-base=1.2.0=h7f98852_2
-  - libxcb=1.13=h7f98852_1003
-  - libxkbcommon=1.0.3=he3ba5ed_0
-  - libxml2=2.9.10=h72842e0_3
-  - llvmlite=0.36.0=py37h9d7f4d0_0
-  - lz4-c=1.9.3=h9c3ff4c_0
-  - markdown=3.3.4=pyhd8ed1ab_0
-  - markupsafe=1.1.1=py37h5e8e339_3
-  - matplotlib-base=3.4.1=py37hdd32ed1_0
-  - mistune=0.8.4=py37h5e8e339_1003
-  - mysql-common=8.0.23=ha770c72_1
-  - mysql-libs=8.0.23=h935591d_1
-  - nbclient=0.5.3=pyhd8ed1ab_0
-  - nbconvert=6.0.7=py37h89c1867_3
-  - nbformat=5.1.3=pyhd8ed1ab_0
-  - ncurses=6.2=h58526e2_4
-  - nest-asyncio=1.5.1=pyhd8ed1ab_0
-  - nettle=3.6=he412f7d_0
-  - notebook=6.3.0=py37h89c1867_0
-  - nspr=4.30=h9c3ff4c_0
-  - nss=3.63=hb5efdd6_0
-  - numba=0.53.1=py37h134767a_0
-  - numpy=1.20.2=py37h038b26d_0
-  - olefile=0.46=pyh9f0ad1d_1
-  - openh264=2.1.1=h780b84a_0
-  - openjpeg=2.4.0=hf7af979_0
-  - openssl=1.1.1k=h7f98852_0
-  - packaging=20.9=pyh44b312d_0
-  - pandas=1.2.3=py37hdc94413_0
-  - pandoc=2.12=h7f98852_0
-  - pandocfilters=1.4.2=py_1
-  - parso=0.8.2=pyhd8ed1ab_0
-  - pcre=8.44=he1b5a44_0
-  - pexpect=4.8.0=pyh9f0ad1d_2
-  - pickleshare=0.7.5=py_1003
-  - pillow=8.1.2=py37h4600e1f_1
-  - pip=21.0.1=pyhd8ed1ab_0
-  - pooch=1.3.0=pyhd8ed1ab_0
-  - prometheus_client=0.10.1=pyhd8ed1ab_0
-  - prompt-toolkit=3.0.18=pyha770c72_0
-  - prompt_toolkit=3.0.18=hd8ed1ab_0
-  - protobuf=3.15.7=py37hcd2ae1e_0
-  - pthread-stubs=0.4=h36c2ea0_1001
-  - ptyprocess=0.7.0=pyhd3deb0d_0
-  - pycparser=2.20=pyh9f0ad1d_2
-  - pygments=2.8.1=pyhd8ed1ab_0
-  - pyopenssl=20.0.1=pyhd8ed1ab_0
-  - pyparsing=2.4.7=pyh9f0ad1d_0
-  - pyqt=5.12.3=py37h89c1867_7
-  - pyqt-impl=5.12.3=py37he336c9b_7
-  - pyqt5-sip=4.19.18=py37hcd2ae1e_7
-  - pyqtchart=5.12=py37he336c9b_7
-  - pyqtwebengine=5.12.1=py37he336c9b_7
-  - pyrsistent=0.17.3=py37h5e8e339_2
-  - pysocks=1.7.1=py37h89c1867_3
-  - pysoundfile=0.10.3.post1=pyhd3deb0d_0
-  - python=3.7.10=hffdb5ce_100_cpython
-  - python-dateutil=2.8.1=py_0
-  - python_abi=3.7=1_cp37m
-  - pytz=2021.1=pyhd8ed1ab_0
-  - pyzmq=22.0.3=py37h336d617_1
-  - qt=5.12.9=hda022c4_4
-  - qtconsole=5.0.3=pyhd8ed1ab_0
-  - qtpy=1.9.0=py_0
-  - readline=8.0=he28a2e2_2
-  - requests=2.25.1=pyhd3deb0d_0
-  - resampy=0.2.2=py_0
-  - scikit-learn=0.24.1=py37h69acf81_0
-  - scipy=1.6.2=py37h29e03ee_0
-  - send2trash=1.5.0=py_0
-  - setuptools=49.6.0=py37h89c1867_3
-  - six=1.15.0=pyh9f0ad1d_0
-  - sqlite=3.35.4=h74cdb3f_0
-  - tensorboard=1.14.0=py37_0
-  - tensorflow=1.14.0=h4531e10_0
-  - tensorflow-base=1.14.0=py37h4531e10_0
-  - tensorflow-estimator=1.14.0=py37h5ca1d4c_0
-  - termcolor=1.1.0=py_2
-  - terminado=0.9.4=py37h89c1867_0
-  - testpath=0.4.4=py_0
-  - threadpoolctl=2.1.0=pyh5ca1d4c_0
-  - tk=8.6.10=h21135ba_1
-  - tornado=6.1=py37h5e8e339_1
-  - traitlets=5.0.5=py_0
-  - typing_extensions=3.7.4.3=py_0
-  - urllib3=1.26.4=pyhd8ed1ab_0
-  - wcwidth=0.2.5=pyh9f0ad1d_2
-  - webencodings=0.5.1=py_1
-  - werkzeug=1.0.1=pyh9f0ad1d_0
-  - wheel=0.36.2=pyhd3deb0d_0
-  - widgetsnbextension=3.5.1=py37h89c1867_4
-  - wrapt=1.12.1=py37h5e8e339_3
-  - x264=1!161.3030=h7f98852_0
-  - xorg-libxau=1.0.9=h7f98852_0
-  - xorg-libxdmcp=1.1.3=h7f98852_0
-  - xz=5.2.5=h516909a_1
-  - zeromq=4.3.4=h9c3ff4c_0
-  - zipp=3.4.1=pyhd8ed1ab_0
-  - zlib=1.2.11=h516909a_1010
-  - zstd=1.4.9=ha95c52a_0
-  - pip:
-    - nvidia-cublas-cu11==11.10.3.66
-    - nvidia-cuda-nvrtc-cu11==11.7.99
-    - nvidia-cuda-runtime-cu11==11.7.99
-    - nvidia-cudnn-cu11==8.5.0.96
-    - torch==1.13.1
-prefix: /home/jacob/miniconda3/envs/species-id
-
diff --git a/conda_environments/environment_Ubuntu20.04.yml b/conda_environments/environment_Ubuntu20.04.yml
deleted file mode 100644
index 104660c..0000000
--- a/conda_environments/environment_Ubuntu20.04.yml
+++ /dev/null
@@ -1,229 +0,0 @@
-name: species-id
-channels:
-  - conda-forge
-  - defaults
-dependencies:
-  - _libgcc_mutex=0.1=conda_forge
-  - _openmp_mutex=4.5=1_gnu
-  - absl-py=0.12.0=pyhd8ed1ab_0
-  - appdirs=1.4.4=pyh9f0ad1d_0
-  - argon2-cffi=20.1.0=py37h5e8e339_2
-  - astor=0.8.1=pyh9f0ad1d_0
-  - async_generator=1.10=py_0
-  - attrs=20.3.0=pyhd3deb0d_0
-  - audioread=2.1.9=py37h89c1867_0
-  - backcall=0.2.0=pyh9f0ad1d_0
-  - backports=1.0=py_2
-  - backports.functools_lru_cache=1.6.3=pyhd8ed1ab_0
-  - bleach=3.3.0=pyh44b312d_0
-  - brotlipy=0.7.0=py37h5e8e339_1001
-  - bzip2=1.0.8=h7f98852_4
-  - c-ares=1.17.1=h7f98852_1
-  - ca-certificates=2021.10.8=ha878542_0
-  - cached-property=1.5.2=hd8ed1ab_1
-  - cached_property=1.5.2=pyha770c72_1
-  - certifi=2021.10.8=py37h89c1867_2
-  - cffi=1.14.5=py37hc58025e_0
-  - chardet=4.0.0=py37h89c1867_1
-  - cryptography=3.4.7=py37h5d9358c_0
-  - cycler=0.10.0=py_2
-  - dbus=1.13.6=h48d8840_2
-  - decorator=5.0.6=pyhd8ed1ab_0
-  - defusedxml=0.7.1=pyhd8ed1ab_0
-  - entrypoints=0.3=pyhd8ed1ab_1003
-  - expat=2.3.0=h9c3ff4c_0
-  - ffmpeg=4.3.1=hca11adc_2
-  - fontconfig=2.13.1=hba837de_1004
-  - freetype=2.10.4=h0708190_1
-  - gast=0.4.0=pyh9f0ad1d_0
-  - gettext=0.19.8.1=h0b5b191_1005
-  - glib=2.68.1=h9c3ff4c_0
-  - glib-tools=2.68.1=h9c3ff4c_0
-  - gmp=6.2.1=h58526e2_0
-  - gnutls=3.6.13=h85f3911_1
-  - google-pasta=0.2.0=pyh8c360ce_0
-  - grpcio=1.37.0=py37hb27c1af_0
-  - gst-plugins-base=1.18.4=h29181c9_0
-  - gstreamer=1.18.4=h76c114f_0
-  - h5py=2.10.0=nompi_py37ha3df211_106
-  - hdf5=1.10.6=nompi_h6a2412b_1114
-  - icu=68.1=h58526e2_0
-  - idna=2.10=pyh9f0ad1d_0
-  - importlib-metadata=3.10.0=py37h89c1867_0
-  - ipykernel=5.5.3=py37h085eea5_0
-  - ipython=7.22.0=py37h085eea5_0
-  - ipython_genutils=0.2.0=py_1
-  - ipywidgets=7.6.3=pyhd3deb0d_0
-  - jedi=0.18.0=py37h89c1867_2
-  - jinja2=2.11.3=pyh44b312d_0
-  - joblib=1.0.1=pyhd8ed1ab_0
-  - jpeg=9d=h36c2ea0_0
-  - jsonschema=3.2.0=pyhd8ed1ab_3
-  - jupyter=1.0.0=py37h89c1867_6
-  - jupyter_client=6.1.12=pyhd8ed1ab_0
-  - jupyter_console=6.4.0=pyhd8ed1ab_0
-  - jupyter_core=4.7.1=py37h89c1867_0
-  - jupyterlab_pygments=0.1.2=pyh9f0ad1d_0
-  - jupyterlab_widgets=1.0.0=pyhd8ed1ab_1
-  - keras-applications=1.0.8=py_1
-  - keras-preprocessing=1.1.2=pyhd8ed1ab_0
-  - kiwisolver=1.3.1=py37h2527ec5_1
-  - krb5=1.17.2=h926e7f8_0
-  - lame=3.100=h7f98852_1001
-  - lcms2=2.12=hddcbb42_0
-  - ld_impl_linux-64=2.35.1=hea4e1c9_2
-  - libblas=3.9.0=8_openblas
-  - libcblas=3.9.0=8_openblas
-  - libcurl=7.76.0=hc4aaa36_0
-  - libedit=3.1.20191231=he28a2e2_2
-  - libev=4.33=h516909a_1
-  - libevent=2.1.10=hcdb4288_3
-  - libffi=3.3=h58526e2_2
-  - libflac=1.3.3=h9c3ff4c_1
-  - libgcc-ng=9.3.0=h2828fa1_18
-  - libgfortran-ng=9.3.0=hff62375_18
-  - libgfortran5=9.3.0=hff62375_18
-  - libglib=2.68.1=h3e27bee_0
-  - libgomp=9.3.0=h2828fa1_18
-  - libiconv=1.16=h516909a_0
-  - liblapack=3.9.0=8_openblas
-  - libllvm10=10.0.1=he513fc3_3
-  - libllvm11=11.1.0=hf817b99_2
-  - libnghttp2=1.43.0=h812cca2_0
-  - libogg=1.3.4=h7f98852_1
-  - libopenblas=0.3.12=pthreads_h4812303_1
-  - libopus=1.3.1=h7f98852_1
-  - libpng=1.6.37=h21135ba_2
-  - libpq=13.1=hfd2b0eb_2
-  - libprotobuf=3.15.7=h780b84a_0
-  - librosa=0.8.0=pyh9f0ad1d_0
-  - libsndfile=1.0.31=h9c3ff4c_1
-  - libsodium=1.0.18=h36c2ea0_1
-  - libssh2=1.9.0=ha56f1ee_6
-  - libstdcxx-ng=9.3.0=h6de172a_18
-  - libtiff=4.2.0=hdc55705_0
-  - libuuid=2.32.1=h7f98852_1000
-  - libvorbis=1.3.7=h9c3ff4c_0
-  - libwebp-base=1.2.0=h7f98852_2
-  - libxcb=1.13=h7f98852_1003
-  - libxkbcommon=1.0.3=he3ba5ed_0
-  - libxml2=2.9.10=h72842e0_3
-  - llvmlite=0.36.0=py37h9d7f4d0_0
-  - lz4-c=1.9.3=h9c3ff4c_0
-  - markdown=3.3.4=pyhd8ed1ab_0
-  - markupsafe=1.1.1=py37h5e8e339_3
-  - matplotlib-base=3.4.1=py37hdd32ed1_0
-  - mistune=0.8.4=py37h5e8e339_1003
-  - mysql-common=8.0.23=ha770c72_1
-  - mysql-libs=8.0.23=h935591d_1
-  - nbclient=0.5.3=pyhd8ed1ab_0
-  - nbconvert=6.0.7=py37h89c1867_3
-  - nbformat=5.1.3=pyhd8ed1ab_0
-  - ncurses=6.2=h58526e2_4
-  - nest-asyncio=1.5.1=pyhd8ed1ab_0
-  - nettle=3.6=he412f7d_0
-  - notebook=6.3.0=py37h89c1867_0
-  - nspr=4.30=h9c3ff4c_0
-  - nss=3.63=hb5efdd6_0
-  - numba=0.53.1=py37h134767a_0
-  - numpy=1.20.2=py37h038b26d_0
-  - olefile=0.46=pyh9f0ad1d_1
-  - openh264=2.1.1=h780b84a_0
-  - openjpeg=2.4.0=hf7af979_0
-  - openssl=1.1.1k=h7f98852_0
-  - packaging=20.9=pyh44b312d_0
-  - pandas=1.2.3=py37hdc94413_0
-  - pandoc=2.12=h7f98852_0
-  - pandocfilters=1.4.2=py_1
-  - parso=0.8.2=pyhd8ed1ab_0
-  - pcre=8.44=he1b5a44_0
-  - pexpect=4.8.0=pyh9f0ad1d_2
-  - pickleshare=0.7.5=py_1003
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-  - pip=21.0.1=pyhd8ed1ab_0
-  - pooch=1.3.0=pyhd8ed1ab_0
-  - prometheus_client=0.10.1=pyhd8ed1ab_0
-  - prompt-toolkit=3.0.18=pyha770c72_0
-  - prompt_toolkit=3.0.18=hd8ed1ab_0
-  - protobuf=3.15.7=py37hcd2ae1e_0
-  - pthread-stubs=0.4=h36c2ea0_1001
-  - ptyprocess=0.7.0=pyhd3deb0d_0
-  - pycparser=2.20=pyh9f0ad1d_2
-  - pygments=2.8.1=pyhd8ed1ab_0
-  - pyopenssl=20.0.1=pyhd8ed1ab_0
-  - pyparsing=2.4.7=pyh9f0ad1d_0
-  - pyqt=5.12.3=py37h89c1867_7
-  - pyqt-impl=5.12.3=py37he336c9b_7
-  - pyqt5-sip=4.19.18=py37hcd2ae1e_7
-  - pyqtchart=5.12=py37he336c9b_7
-  - pyqtwebengine=5.12.1=py37he336c9b_7
-  - pyrsistent=0.17.3=py37h5e8e339_2
-  - pysocks=1.7.1=py37h89c1867_3
-  - pysoundfile=0.10.3.post1=pyhd3deb0d_0
-  - python=3.7.10=hffdb5ce_100_cpython
-  - python-dateutil=2.8.1=py_0
-  - python_abi=3.7=1_cp37m
-  - pytz=2021.1=pyhd8ed1ab_0
-  - pyzmq=22.0.3=py37h336d617_1
-  - qt=5.12.9=hda022c4_4
-  - qtconsole=5.0.3=pyhd8ed1ab_0
-  - qtpy=1.9.0=py_0
-  - readline=8.0=he28a2e2_2
-  - requests=2.25.1=pyhd3deb0d_0
-  - resampy=0.2.2=py_0
-  - scikit-learn=0.24.1=py37h69acf81_0
-  - scipy=1.6.2=py37h29e03ee_0
-  - send2trash=1.5.0=py_0
-  - setuptools=49.6.0=py37h89c1867_3
-  - six=1.15.0=pyh9f0ad1d_0
-  - sqlite=3.35.4=h74cdb3f_0
-  - termcolor=1.1.0=py_2
-  - terminado=0.9.4=py37h89c1867_0
-  - testpath=0.4.4=py_0
-  - threadpoolctl=2.1.0=pyh5ca1d4c_0
-  - tk=8.6.10=h21135ba_1
-  - tornado=6.1=py37h5e8e339_1
-  - traitlets=5.0.5=py_0
-  - typing_extensions=3.7.4.3=py_0
-  - urllib3=1.26.4=pyhd8ed1ab_0
-  - wcwidth=0.2.5=pyh9f0ad1d_2
-  - webencodings=0.5.1=py_1
-  - werkzeug=1.0.1=pyh9f0ad1d_0
-  - wheel=0.36.2=pyhd3deb0d_0
-  - widgetsnbextension=3.5.1=py37h89c1867_4
-  - wrapt=1.12.1=py37h5e8e339_3
-  - x264=1!161.3030=h7f98852_0
-  - xorg-libxau=1.0.9=h7f98852_0
-  - xorg-libxdmcp=1.1.3=h7f98852_0
-  - xz=5.2.5=h516909a_1
-  - zeromq=4.3.4=h9c3ff4c_0
-  - zipp=3.4.1=pyhd8ed1ab_0
-  - zlib=1.2.11=h516909a_1010
-  - zstd=1.4.9=ha95c52a_0
-  - pip:
-      - astunparse==1.6.3
-      - cachetools==5.0.0
-      - flatbuffers==2.0
-      - google-auth==2.6.6
-      - google-auth-oauthlib==0.4.6
-      - keras==2.8.0
-      - libclang==14.0.1
-      - nvidia-cublas-cu11==11.10.3.66
-      - nvidia-cuda-nvrtc-cu11==11.7.99
-      - nvidia-cuda-runtime-cu11==11.7.99
-      - nvidia-cudnn-cu11==8.5.0.96
-      - oauthlib==3.2.0
-      - opt-einsum==3.3.0
-      - pyasn1==0.4.8
-      - pyasn1-modules==0.2.8
-      - requests-oauthlib==1.3.1
-      - rsa==4.8
-      - seaborn==0.11.2
-      - tensorboard==2.8.0
-      - tensorboard-data-server==0.6.1
-      - tensorboard-plugin-wit==1.8.1
-      - tensorflow==2.8.0
-      - tensorflow-io-gcs-filesystem==0.25.0
-      - tf-estimator-nightly==2.8.0.dev2021122109
-      - torch==1.13.1
-prefix: /home/jacob/miniconda3/envs/species-id
diff --git a/conda_environments/environment_Windows10.yml b/conda_environments/environment_Windows10.yml
deleted file mode 100644
index 5159056..0000000
--- a/conda_environments/environment_Windows10.yml
+++ /dev/null
@@ -1,196 +0,0 @@
-name: species-id
-channels:
-  - conda-forge
-  - defaults
-dependencies:
-  - absl-py=0.12.0=pyhd8ed1ab_0
-  - appdirs=1.4.4=pyh9f0ad1d_0
-  - argon2-cffi=20.1.0=py37hcc03f2d_2
-  - astor=0.8.1=pyh9f0ad1d_0
-  - async_generator=1.10=py_0
-  - attrs=20.3.0=pyhd3deb0d_0
-  - audioread=2.1.9=py37h03978a9_0
-  - backcall=0.2.0=pyh9f0ad1d_0
-  - backports=1.0=py_2
-  - backports.functools_lru_cache=1.6.4=pyhd8ed1ab_0
-  - bleach=3.3.0=pyh44b312d_0
-  - brotlipy=0.7.0=py37hcc03f2d_1001
-  - ca-certificates=2020.12.5=h5b45459_0
-  - cached-property=1.5.2=hd8ed1ab_1
-  - cached_property=1.5.2=pyha770c72_1
-  - certifi=2020.12.5=py37h03978a9_1
-  - cffi=1.14.5=py37hd8e9650_0
-  - chardet=4.0.0=py37h03978a9_1
-  - colorama=0.4.4=pyh9f0ad1d_0
-  - cryptography=3.4.7=py37h20c650d_0
-  - cycler=0.10.0=py_2
-  - decorator=5.0.7=pyhd8ed1ab_0
-  - defusedxml=0.7.1=pyhd8ed1ab_0
-  - entrypoints=0.3=pyhd8ed1ab_1003
-  - ffmpeg=4.2.2=he774522_0
-  - freetype=2.10.4=h546665d_1
-  - gast=0.4.0=pyh9f0ad1d_0
-  - google-pasta=0.2.0=pyh8c360ce_0
-  - grpcio=1.37.0=py37h04d2302_0
-  - h5py=2.10.0=nompi_py37he280515_106
-  - hdf5=1.10.6=nompi_h5268f04_1114
-  - icu=68.1=h0e60522_0
-  - idna=2.10=pyh9f0ad1d_0
-  - importlib-metadata=4.0.1=py37h03978a9_0
-  - intel-openmp=2021.2.0=h57928b3_616
-  - ipykernel=5.5.3=py37h7813e69_0
-  - ipython=7.22.0=py37h7813e69_0
-  - ipython_genutils=0.2.0=py_1
-  - ipywidgets=7.6.3=pyhd3deb0d_0
-  - jedi=0.18.0=py37h03978a9_2
-  - jinja2=2.11.3=pyh44b312d_0
-  - joblib=1.0.1=pyhd8ed1ab_0
-  - jpeg=9d=h8ffe710_0
-  - jsonschema=3.2.0=pyhd8ed1ab_3
-  - jupyter=1.0.0=py37h03978a9_6
-  - jupyter_client=6.1.12=pyhd8ed1ab_0
-  - jupyter_console=6.4.0=pyhd8ed1ab_0
-  - jupyter_core=4.7.1=py37h03978a9_0
-  - jupyterlab_pygments=0.1.2=pyh9f0ad1d_0
-  - jupyterlab_widgets=1.0.0=pyhd8ed1ab_1
-  - keras-applications=1.0.8=py_1
-  - keras-preprocessing=1.1.2=pyhd8ed1ab_0
-  - kiwisolver=1.3.1=py37h8c56517_1
-  - krb5=1.17.2=hbae68bd_0
-  - lcms2=2.12=h2a16943_0
-  - libblas=3.9.0=8_mkl
-  - libcblas=3.9.0=8_mkl
-  - libclang=11.1.0=default_h5c34c98_0
-  - libcurl=7.76.1=hf1763fc_1
-  - libflac=1.3.3=h0e60522_1
-  - liblapack=3.9.0=8_mkl
-  - libogg=1.3.4=h8ffe710_1
-  - libopus=1.3.1=h8ffe710_1
-  - libpng=1.6.37=h1d00b33_2
-  - libprotobuf=3.15.8=h7755175_0
-  - librosa=0.8.0=pyh9f0ad1d_0
-  - libsndfile=1.0.31=h0e60522_1
-  - libsodium=1.0.18=h8d14728_1
-  - libssh2=1.9.0=h680486a_6
-  - libtiff=4.2.0=hc10be44_1
-  - libvorbis=1.3.7=h0e60522_0
-  - llvmlite=0.36.0=py37habb0c8c_0
-  - lz4-c=1.9.3=h8ffe710_0
-  - m2w64-gcc-libgfortran=5.3.0=6
-  - m2w64-gcc-libs=5.3.0=7
-  - m2w64-gcc-libs-core=5.3.0=7
-  - m2w64-gmp=6.1.0=2
-  - m2w64-libwinpthread-git=5.0.0.4634.697f757=2
-  - markdown=3.3.4=pyhd8ed1ab_0
-  - markupsafe=1.1.1=py37hcc03f2d_3
-  - matplotlib=3.4.1=py37h03978a9_0
-  - matplotlib-base=3.4.1=py37h0d1fb12_0
-  - mistune=0.8.4=py37hcc03f2d_1003
-  - mkl=2020.4=hb70f87d_311
-  - msys2-conda-epoch=20160418=1
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-  - notebook=6.3.0=pyha770c72_1
-  - numba=0.53.1=py37h4e635f9_0
-  - numpy=1.20.2=py37hcbcd69c_0
-  - olefile=0.46=pyh9f0ad1d_1
-  - openjpeg=2.4.0=h48faf41_0
-  - openssl=1.1.1k=h8ffe710_0
-  - packaging=20.9=pyh44b312d_0
-  - pandas=1.2.4=py37h90003fb_0
-  - pandoc=2.13=h8ffe710_0
-  - pandocfilters=1.4.2=py_1
-  - parso=0.8.2=pyhd8ed1ab_0
-  - pickleshare=0.7.5=py_1003
-  - pillow=8.1.2=py37h96663a1_1
-  - pip=21.0.1=pyhd8ed1ab_0
-  - pooch=1.3.0=pyhd8ed1ab_0
-  - prometheus_client=0.10.1=pyhd8ed1ab_0
-  - prompt-toolkit=3.0.18=pyha770c72_0
-  - prompt_toolkit=3.0.18=hd8ed1ab_0
-  - protobuf=3.15.8=py37hf2a7229_0
-  - pycparser=2.20=pyh9f0ad1d_2
-  - pygments=2.8.1=pyhd8ed1ab_0
-  - pyopenssl=20.0.1=pyhd8ed1ab_0
-  - pyparsing=2.4.7=pyh9f0ad1d_0
-  - pyqt=5.12.3=py37h03978a9_7
-  - pyqt-impl=5.12.3=py37hf2a7229_7
-  - pyqt5-sip=4.19.18=py37hf2a7229_7
-  - pyqtchart=5.12=py37hf2a7229_7
-  - pyqtwebengine=5.12.1=py37hf2a7229_7
-  - pyreadline=2.1=py37h03978a9_1003
-  - pyrsistent=0.17.3=py37hcc03f2d_2
-  - pysocks=1.7.1=py37h03978a9_3
-  - pysoundfile=0.10.3.post1=pyhd3deb0d_0
-  - python=3.7.10=h7840368_100_cpython
-  - python-dateutil=2.8.1=py_0
-  - python_abi=3.7=1_cp37m
-  - pytz=2021.1=pyhd8ed1ab_0
-  - pywin32=300=py37hcc03f2d_0
-  - pywinpty=0.5.7=py37h03978a9_1
-  - pyzmq=22.0.3=py37hcce574b_1
-  - qt=5.12.9=h5909a2a_4
-  - qtconsole=5.0.3=pyhd8ed1ab_0
-  - qtpy=1.9.0=py_0
-  - requests=2.25.1=pyhd3deb0d_0
-  - resampy=0.2.2=py_0
-  - scikit-learn=0.24.1=py37heb15398_0
-  - scipy=1.6.2=py37h924764e_0
-  - send2trash=1.5.0=py_0
-  - setuptools=49.6.0=py37h03978a9_3
-  - six=1.15.0=pyh9f0ad1d_0
-  - sqlite=3.35.5=h8ffe710_0
-  - termcolor=1.1.0=py_2
-  - terminado=0.9.4=py37h03978a9_0
-  - testpath=0.4.4=py_0
-  - threadpoolctl=2.1.0=pyh5ca1d4c_0
-  - tk=8.6.10=h8ffe710_1
-  - tornado=6.1=py37hcc03f2d_1
-  - traitlets=5.0.5=py_0
-  - typing_extensions=3.7.4.3=py_0
-  - urllib3=1.26.4=pyhd8ed1ab_0
-  - vc=14.2=hb210afc_4
-  - vs2015_runtime=14.28.29325=h5e1d092_4
-  - wcwidth=0.2.5=pyh9f0ad1d_2
-  - webencodings=0.5.1=py_1
-  - werkzeug=1.0.1=pyh9f0ad1d_0
-  - wheel=0.36.2=pyhd3deb0d_0
-  - widgetsnbextension=3.5.1=py37h03978a9_4
-  - win_inet_pton=1.1.0=py37h03978a9_2
-  - wincertstore=0.2=py37h03978a9_1006
-  - winpty=0.4.3=4
-  - wrapt=1.12.1=py37hcc03f2d_3
-  - xz=5.2.5=h62dcd97_1
-  - zeromq=4.3.4=h0e60522_0
-  - zipp=3.4.1=pyhd8ed1ab_0
-  - zlib=1.2.11=h62dcd97_1010
-  - zstd=1.4.9=h6255e5f_0
-  - pip:
-    - astunparse==1.6.3
-    - cachetools==5.0.0
-    - flatbuffers==2.0
-    - google-auth==2.6.6
-    - google-auth-oauthlib==0.4.6
-    - keras==2.8.0
-    - libclang==14.0.1
-    - nvidia-cublas-cu11==11.10.3.66
-    - nvidia-cuda-nvrtc-cu11==11.7.99
-    - nvidia-cuda-runtime-cu11==11.7.99
-    - nvidia-cudnn-cu11==8.5.0.96
-    - oauthlib==3.2.0
-    - opt-einsum==3.3.0
-    - pyasn1==0.4.8
-    - pyasn1-modules==0.2.8
-    - requests-oauthlib==1.3.1
-    - rsa==4.8
-    - seaborn==0.11.2
-    - tensorboard==2.8.0
-    - tensorboard-data-server==0.6.1
-    - tensorboard-plugin-wit==1.8.1
-    - tensorflow==2.8.0
-    - tensorflow-io-gcs-filesystem==0.25.0
-    - tf-estimator-nightly==2.8.0.dev2021122109
-    - torch==1.13.1
-prefix: C:\Users\Jacob\miniconda3\envs\species-id
diff --git a/conda_environments/environment_tweety_Windows10.yml b/conda_environments/environment_tweety_Windows10.yml
deleted file mode 100644
index 85e0389..0000000
Binary files a/conda_environments/environment_tweety_Windows10.yml and /dev/null differ
diff --git a/conda_environments/windows_environment_Tweety.yml b/conda_environments/windows_environment_Tweety.yml
deleted file mode 100644
index 117985e..0000000
Binary files a/conda_environments/windows_environment_Tweety.yml and /dev/null differ
diff --git a/poetry.lock b/poetry.lock
new file mode 100644
index 0000000..28d9055
--- /dev/null
+++ b/poetry.lock
@@ -0,0 +1,4594 @@
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+[[package]]
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+[package.extras]
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+[[package]]
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+[[package]]
+name = "zipp"
+version = "3.17.0"
+description = "Backport of pathlib-compatible object wrapper for zip files"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "zipp-3.17.0-py3-none-any.whl", hash = "sha256:0e923e726174922dce09c53c59ad483ff7bbb8e572e00c7f7c46b88556409f31"},
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+
+[package.extras]
+docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-lint"]
+testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"]
+
+[metadata]
+lock-version = "2.0"
+python-versions = ">=3.8,<3.11"
+content-hash = "c3c477d794e35255310d81b8c3da8ba286d9c6782a724496af086809b6637402"
diff --git a/pyha_tests/conftest.py b/pyha_tests/conftest.py
new file mode 100644
index 0000000..09a94cb
--- /dev/null
+++ b/pyha_tests/conftest.py
@@ -0,0 +1,58 @@
+'''Test Fixtures
+'''
+import json
+import os
+import shutil
+from pathlib import Path
+from tempfile import TemporaryDirectory
+from typing import Dict
+
+import pytest
+from nas_unzip.nas import nas_unzip
+
+
+@pytest.fixture(name='creds', scope='session')
+def create_creds() -> Dict[str, str]:
+    """Obtains the credentials
+
+    Returns:
+        Dict[str, str]: Username and password dictionary
+    """
+    if Path('credentials.json').is_file():
+        with open('credentials.json', 'r', encoding='ascii') as handle:
+            return json.load(handle)
+    else:
+        value = os.environ['NAS_CREDS'].splitlines()
+        assert len(value) == 2
+        return {
+            'username': value[0],
+            'password': value[1]
+        }
+
+
+@pytest.fixture(name='reference_data', scope='session')
+def create_reference_data(creds) -> Path:
+    """Creates reference data
+
+    Args:
+        creds (Dict[str, str]): NAS Credentials
+
+    Returns:
+        Path: Path to data
+
+    Yields:
+        Iterator[Path]: Path to data
+    """
+    with TemporaryDirectory() as tmp_dir:
+        path = Path(tmp_dir).resolve()
+        if not Path('TEST').is_dir():
+            nas_unzip(
+                network_path='smb://e4e-nas.ucsd.edu:6021/temp/github_actions/pyha/pyha_test.zip',
+                output_path=path,
+                username=creds['username'],
+                password=creds['password']
+            )
+            yield path.joinpath('pyha_test')
+        else:
+            shutil.copytree(Path('TEST'), path, dirs_exist_ok=True)
+            yield path
diff --git a/pyha_tests/test_imports.py b/pyha_tests/test_imports.py
new file mode 100644
index 0000000..c741c22
--- /dev/null
+++ b/pyha_tests/test_imports.py
@@ -0,0 +1,84 @@
+'''Tests PyHa environment
+'''
+import json
+import os
+from pathlib import Path
+from tempfile import TemporaryDirectory
+from typing import Dict
+
+from nas_unzip.nas import nas_unzip
+import torch
+
+from PyHa.IsoAutio import generate_automated_labels
+
+
+def create_creds() -> Dict[str, str]:
+    """Obtains the credentials
+
+    Returns:
+        Dict[str, str]: Username and password dictionary
+    """
+    if Path('credentials.json').is_file():
+        with open('credentials.json', 'r', encoding='ascii') as handle:
+            return json.load(handle)
+    else:
+        value = os.environ['NAS_CREDS'].splitlines()
+        assert len(value) == 2
+        return {
+            'username': value[0],
+            'password': value[1]
+        }
+
+
+def run_pyha(creds):
+    """Tests PyHa
+    """
+    with TemporaryDirectory() as path:
+        nas_unzip(
+            network_path='smb://e4e-nas.ucsd.edu:6021/temp/github_actions/pyha/pyha_test.zip',
+            output_path=Path(path),
+            username=creds['username'],
+            password=creds['password']
+        )
+        isolation_parameters = {
+            "model": "tweetynet",
+            "tweety_output": True,
+            "technique": "steinberg",
+            "threshold_type": "median",
+            "threshold_const": 2.0,
+            "threshold_min": 0.0,
+            "window_size": 2.0,
+            "chunk_size": 5.0,
+            "verbose": True
+        }
+        # generate_automated_labels(path, isolation_parameters)
+        # isolation_parameters = {
+        #     "model": "birdnet",
+        #     "output_path": "outputs",
+        #     "lat": 35.4244,
+        #     "lon": -120.7463,
+        #     "week": 18,
+        #     "min_conf": 0.1,
+        #     "filetype": "wav",
+        #     "num_predictions": 1,
+        #     "write_to_csv": False,
+        # }
+        # generate_automated_labels(path, isolation_parameters)
+        # isolation_parameters = {
+        #     "model":          "microfaune",
+        #     "technique":       "steinberg",
+        #     "threshold_type":  "median",
+        #     "threshold_const": 2.0,
+        #     "threshold_min":   0.0,
+        #     "window_size":     2.0,
+        #     "chunk_size":      5.0,
+        #     "verbose":     True
+        # }
+        # generate_automated_labels(path, isolation_parameters)
+
+def main():
+    creds = create_creds()
+    run_pyha(creds)
+
+if __name__ == '__main__':
+    main()
\ No newline at end of file
diff --git a/pyha_tests/test_pyha.py b/pyha_tests/test_pyha.py
new file mode 100644
index 0000000..34c4252
--- /dev/null
+++ b/pyha_tests/test_pyha.py
@@ -0,0 +1,68 @@
+'''Tests PyHa environment
+'''
+from pathlib import Path
+import importlib
+
+from PyHa.IsoAutio import generate_automated_labels
+
+
+def test_reference_data(reference_data: Path):
+    """Tests that the reference data is sane
+
+    Args:
+        reference_data (Path): Path to reference data
+    """
+    for i in range(11):
+        assert reference_data.joinpath(f'ScreamingPiha{i + 1}.wav').exists()
+
+def test_resampy_installed():
+    try:
+        importlib.import_module('resampy')
+        assert True  # resampy is installed
+    except ImportError:
+        assert False, "resampy is not installed"
+        
+def test_pyha(reference_data: Path):
+    """Tests PyHa
+    """
+    
+    isolation_parameters = {
+        "model": "tweetynet",
+        "tweety_output": True,
+        "technique": "steinberg",
+        "threshold_type": "median",
+        "threshold_const": 2.0,
+        "threshold_min": 0.0,
+        "window_size": 2.0,
+        "chunk_size": 5.0,
+        "verbose": True
+    }
+    df = generate_automated_labels(reference_data.as_posix() + '/', isolation_parameters)
+    assert df.empty != True
+
+    isolation_parameters = {
+        "model": "birdnet",
+        "output_path": "outputs",
+        "lat": 35.4244,
+        "lon": -120.7463,
+        "week": 18,
+        "min_conf": 0.1,
+        "filetype": "wav",
+        "num_predictions": 1,
+        "write_to_csv": False,
+    }
+    df = generate_automated_labels(reference_data.as_posix() + '/', isolation_parameters)
+    assert df.empty != True
+
+    isolation_parameters = {
+        "model":          "microfaune",
+        "technique":       "steinberg",
+        "threshold_type":  "median",
+        "threshold_const": 2.0,
+        "threshold_min":   0.0,
+        "window_size":     2.0,
+        "chunk_size":      5.0,
+        "verbose":     True
+    }
+    df = generate_automated_labels(reference_data.as_posix() + '/', isolation_parameters)
+    assert df.empty != True 
\ No newline at end of file
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..787f532
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,63 @@
+[tool.poetry]
+name = "PyHa"
+version = "0.0.0"
+description = "PyHa"
+authors = [
+    "UCSD Engineers for Exploration <e4e@ucsd.edu>",
+    "Jacob Ayers <jgayers@ucsd.edu>",
+    "Natalie Franklin",
+    "Sam Prestrelski <sprestrelski@ucsd.edu>",
+    "Sean Perry <shperry@ucsd.edu>",
+    "Mugen Blue",
+    "Nishant Balaji",
+    "Teo Maldonado",
+    "Vanessa Salgado",
+    "Pranjal Chatterjee",
+    "Shreyas Anantha Ramaprasad",
+    "Shravan Konduru",
+    "Benjamin Cates"
+]
+license = "CC-BY-NC-SA-4.0"
+readme = "README.md"
+repository = 'https://github.com/UCSD-E4E/PyHa'
+packages = [
+    {include = "PyHa"}
+]
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"
+
+[tool.poetry.group.dev.dependencies]
+pylint = "^3.0.2"
+pytest = "^7.4.3"
+nas_unzip = { git="https://github.com/UCSD-E4E/synology-download.git", rev="dcca086" }
+synology-api = "0.5.1"
+autopep8 = "^2.0.4"
+
+[tool.poetry.dependencies]
+python = ">=3.8,<3.11"
+librosa = "^0.10.1"
+jupyter = "^1.0.0"
+scikit-learn = "^1.3.2"
+seaborn = "^0.13.0"
+keras = "^2.8.0"
+pandas = "^2.0.0"
+matplotlib = "^3.4.1"
+scipy = "^1.6.2"
+# See https://github.com/pytorch/pytorch/issues/100974
+torch =  ">=2.0.0, !=2.0.1, !=2.1.0"
+# see https://github.com/python-poetry/poetry/issues/8271
+tensorflow = {version = "^2.13.0" }
+tensorflow-macos = { version = "^2.13.0", platform = "darwin", markers = "platform_machine=='arm64'" }
+tensorflow-intel = { version = "2.13.0", platform = "win32" }
+tensorflow-cpu = [
+    { version = "^2.13.0", platform = "linux", markers = "platform_machine!='arm64' and platform_machine!='aarch64'" },
+    { version = "^2.13.0", platform = "darwin", markers = "platform_machine!='arm64' and platform_machine!='aarch64'" },
+]
+tensorflow-cpu-aws = { version = "^2.13.0", platform = "linux", markers = "platform_machine=='arm64' or platform_machine=='aarch64'" }
+tensorflow-io-gcs-filesystem = [
+    { version = ">= 0.23.1", markers = "platform_machine!='arm64' or platform_system!='Darwin'" },
+    { version = "< 0.32.0", markers = "platform_system == 'Windows'" }
+]
+resampy = "^0.4.2"