support SAM-Med2D

README_us-EN.md

@@ -38,6 +38,7 @@ English | [简体中文](README_zh-CN.md)
 - Segment Anything Model
   - [SAM](https://arxiv.org/abs/2304.02643): Universal model for natural image segmentation;
   - [MobileSAM](https://arxiv.org/abs/2306.14289): Faster version of `SAM`;
+  - [SAM-Med2D](https://github.com/OpenGVLab/SAM-Med2D): 2D Universal model for medical image segmentation (🤗); 
   - [MedSAM](https://arxiv.org/abs/2304.12306): Universal model for medical image segmentation;
   - [LVMSAM](https://arxiv.org/abs/2306.11925)
     - [BUID](https://github.com/CVHub520/X-AnyLabeling/tree/main/assets/examples/buid): Ultrasound breast cancer segmentation model;
@@ -65,7 +66,7 @@ English | [简体中文](README_zh-CN.md)
 
 ### 1.1 Executable
 
-- Download and run the `GUI` version directly from [Baidu Cloud (Access Code: bkdj)](https://pan.baidu.com/s/1cJeRE2wdiYDy05pb5_JqYQ?pwd=bkdj).
+- Download and run the `GUI` version directly from [Release tag-v0.2.1](https://github.com/CVHub520/X-AnyLabeling/releases/tag/v0.2.1).
 
 Note:
 - For MacOS:

README_zh-CN.md

@@ -14,7 +14,7 @@
 <div align="center">
 
 
-[帮助文档](./docs/Q&A.md)
+👉[帮助文档](./docs/Q&A.md)👈
 
 简体中文 | [English](README_us-EN.md)
 
@@ -41,6 +41,7 @@
 - Segment Anything Model
   - [SAM](https://arxiv.org/abs/2304.02643): 通用自然图像分割一切模型；
   - [MobileSAM](https://arxiv.org/abs/2306.14289): 快速版 `SAM`；
+  - [SAM-Med2D](https://github.com/OpenGVLab/SAM-Med2D): 2D医学图像分割一切模型（🤗推荐）;
   - [MedSAM](https://arxiv.org/abs/2304.12306): 通用医学图像分割一切模型；
   - [LVMSAM](https://arxiv.org/abs/2306.11925)
       - [BUID](https://github.com/CVHub520/X-AnyLabeling/tree/main/assets/examples/buid): 超声乳腺癌分割模型；
@@ -69,7 +70,7 @@
 
 ### 1.1 可执行文件
 
-- 从[百度网盘(提取码: bkdj)](https://pan.baidu.com/s/1cJeRE2wdiYDy05pb5_JqYQ?pwd=bkdj)下载并运行`GUI`版本直接运行。
+- 从[百度网盘(提取码: cn0c)](https://pan.baidu.com/s/1HeEoVc-_DI5EuSU3MipqJQ?pwd=cn0c)下载并运行`GUI`版本直接运行。
 
 注意：
 - 对于MacOS：

anylabeling/app_info.py

@@ -1,4 +1,4 @@
 __appname__ = "X-AnyLabeling"
 __appdescription__ = "Advanced Auto Labeling Solution with Added Features"
-__version__ = "0.2.0"
+__version__ = "0.2.1"
 __preferred_device__ = "CPU"  # GPU or CPU

anylabeling/configs/auto_labeling/models.yaml

@@ -1,3 +1,5 @@
+- model_name: "sam_med2d_vit_b-r20230901"
+  config_file: ":/sam_med2d_vit_b.yaml"
 - model_name: "segment_anything_vit_b_quant-r20230810"
   config_file: ":/segment_anything_vit_b_quant.yaml"
 - model_name: "segment_anything_vit_b-r20230810"
@@ -28,6 +30,14 @@
   config_file: ":/medsam_vit_b_quant.yaml"
 - model_name: "mobile_sam_vit_h-r20230810"
   config_file: ":/mobile_sam_vit_h.yaml"
+- model_name: "clrnet_tusimple_r18-r20230901"
+  config_file: ":/clrnet_tusimple_r18.yaml"
+- model_name: "yolox_l_dwpose_ucoco-r20230820"
+  config_file: ":/yolox_l_dwpose_ucoco.yaml"
+- model_name: "rtdetr_r50-r20230520"
+  config_file: ":/rtdetr_r50.yaml"
+- model_name: "yolov5s_resnet50-r20230520"
+  config_file: ":/yolov5s_resnet50.yaml"
 - model_name: "yolov5n-r20230520"
   config_file: ":/yolov5n.yaml"
 - model_name: "yolov5s-r20230520"
@@ -81,12 +91,4 @@
 - model_name: "yolo-nas-m-r20230615"
   config_file: ":/yolo_nas_m.yaml"
 - model_name: "yolo-nas-l-r20230615"
-  config_file: ":/yolo_nas_l.yaml"
-- model_name: "yolov5s_resnet50-r20230520"
-  config_file: ":/yolov5s_resnet50.yaml"
-- model_name: "rtdetr_r50-r20230520"
-  config_file: ":/rtdetr_r50.yaml"
-- model_name: "yolox_l_dwpose_ucoco-r20230820"
-  config_file: ":/yolox_l_dwpose_ucoco.yaml"
-- model_name: "clrnet_tusimple_r18-r20230901"
-  config_file: ":/clrnet_tusimple_r18.yaml"
+  config_file: ":/yolo_nas_l.yaml"

anylabeling/configs/auto_labeling/sam_med2d_vit_b.yaml

@@ -0,0 +1,6 @@
+type: sam_med2d
+name: sam-med2d_vit_b-r20230901
+display_name: SAM-Med2D-256x (ViT-Base)
+encoder_model_path: https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.2.0/sam-med2d_b.encoder.onnx
+decoder_model_path: https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.2.0/sam-med2d_b.decoder.onnx
+input_size: 256

anylabeling/services/auto_labeling/model.py

@@ -30,7 +30,7 @@
 
 class Model(QObject):
     BASE_DOWNLOAD_URL = (
-        "https://github.com/CVHub520/X-AnyLabeling/releases/tag/v0.2.0"
+        "https://github.com/CVHub520/X-AnyLabeling/releases/tag/v0.2.1"
     )
 
     class Meta(QObject):

anylabeling/services/auto_labeling/model_manager.py

@@ -165,7 +165,8 @@ def load_custom_model(self, config_file):
             or "name" not in model_config
             or model_config["type"]
             not in [
-                "segment_anything", 
+                "segment_anything",
+                "sam_med2d",
                 "yolov5", 
                 "yolov6", 
                 "yolov7", 
@@ -455,7 +456,30 @@ def _load_model(self, model_id):
                     )
                 )
                 return
+            # Request next files for prediction
+            self.request_next_files_requested.emit()
+        elif model_config["type"] == "sam_med2d":
+            from .sam_med2d import SAM_Med2D
 
+            try:
+                model_config["model"] = SAM_Med2D(
+                    model_config, on_message=self.new_model_status.emit
+                )
+                self.auto_segmentation_model_selected.emit()
+            except Exception as e:  # noqa
+                print(
+                    "Error in loading model: {error_message}".format(
+                        error_message=str(e)
+                    )
+                )
+                self.new_model_status.emit(
+                    self.tr(
+                        "Error in loading model: {error_message}".format(
+                            error_message=str(e)
+                        )
+                    )
+                )
+                return
             # Request next files for prediction
             self.request_next_files_requested.emit()
         elif model_config["type"] == "yolov5_cls":
@@ -580,7 +604,7 @@ def set_auto_labeling_marks(self, marks):
         """
         if (
             self.loaded_model_config is None
-            or self.loaded_model_config["type"] != "segment_anything"
+            or self.loaded_model_config["type"] not in ["segment_anything", "sam_med2d"]
         ):
             return
         self.loaded_model_config["model"].set_auto_labeling_marks(marks)
@@ -666,8 +690,8 @@ def on_next_files_changed(self, next_files):
         if self.loaded_model_config is None:
             return
 
-        # Currently only segment_anything model supports this feature
-        if self.loaded_model_config["type"] != "segment_anything":
+        # Currently only segment_anything-like model supports this feature
+        if self.loaded_model_config["type"] not in ["segment_anything", "sam_med2d"]:
             return
 
         self.loaded_model_config["model"].on_next_files_changed(next_files)