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"version": "==5.14.0" + }, + "wcwidth": { + "hashes": [ + "sha256:f01c104efdf57971bcb756f054dd58ddec5204dd15fa31d6503ea57947d97c02", + "sha256:f26ec43d96c8cbfed76a5075dac87680124fa84e0855195a6184da9c187f133c" + ], + "version": "==0.2.12" + } + } +} diff --git a/client/package.json b/client/package.json index 0fb5452..a056410 100644 --- a/client/package.json +++ b/client/package.json @@ -18,6 +18,7 @@ "@radix-ui/react-avatar": "^1.0.4", "@radix-ui/react-checkbox": "^1.0.4", "@radix-ui/react-context-menu": "^2.1.5", + "@radix-ui/react-dialog": "^1.0.5", "@radix-ui/react-dropdown-menu": "^2.0.6", "@radix-ui/react-icons": "^1.3.0", "@radix-ui/react-label": "^2.0.2", diff --git a/client/pnpm-lock.yaml b/client/pnpm-lock.yaml index 63619f1..925ca5a 100644 --- a/client/pnpm-lock.yaml +++ b/client/pnpm-lock.yaml @@ -23,6 +23,9 @@ dependencies: '@radix-ui/react-context-menu': specifier: ^2.1.5 version: 2.1.5(@types/react-dom@18.2.7)(@types/react@18.2.21)(react-dom@18.2.0)(react@18.2.0) + '@radix-ui/react-dialog': + specifier: ^1.0.5 + version: 1.0.5(@types/react-dom@18.2.7)(@types/react@18.2.21)(react-dom@18.2.0)(react@18.2.0) '@radix-ui/react-dropdown-menu': specifier: ^2.0.6 version: 2.0.6(@types/react-dom@18.2.7)(@types/react@18.2.21)(react-dom@18.2.0)(react@18.2.0) diff --git a/client/src/api/index.ts b/client/src/api/index.ts new file mode 100644 index 0000000..983894f --- /dev/null +++ b/client/src/api/index.ts @@ -0,0 +1,4 @@ +import { sfu } from './sfu'; +import { stableDiffusion } from './stableDiffusion'; + +export { sfu, stableDiffusion }; diff --git a/client/src/api/sfu.ts b/client/src/api/sfu.ts new file mode 100644 index 0000000..725a0ce --- /dev/null +++ b/client/src/api/sfu.ts @@ -0,0 +1,25 @@ +import { REST } from '@/constants'; +import axios from 'axios'; + +/** + * Defines REST methods for the SFU API. + * @author Yousef Yassin + */ + +/** + * Function to poll for an ongoing stream in a room and initialize a consumer if available. + * @param roomID String, the ID of the room to poll. + * @param initConsumer Function, callback to initialize the consumer when a stream is available. + */ +const pollOngoingStream = async (roomID: string, initConsumer: () => void) => { + try { + const { data } = await axios.put(REST.sfu.poll, { + roomId: roomID, + }); + data.roomHasProducer && initConsumer(); + } catch (e) { + console.error('Failed to poll for ongoing stream'); + } +}; + +export const sfu = { poll: pollOngoingStream }; diff --git a/client/src/api/stableDiffusion.ts b/client/src/api/stableDiffusion.ts new file mode 100644 index 0000000..5938f4a --- /dev/null +++ b/client/src/api/stableDiffusion.ts @@ -0,0 +1,28 @@ +import axios from 'axios'; + +/** + * Defines REST methods for the Stable Diffusion API. + * @author Yousef Yassin + */ + +/** + * Sends a textual prompt and an image, as a dataURL, to the server + * to perform stable diffusion. Return the generated images. + * TODO: Add more options here. / more methods to set models. + * @param prompt The textual prompt. + * @param dataURL The image to condition on. + * @returns The generated images { image_data_urls: string[] }. + */ +const diffusion = async (prompt: string, dataURL: string) => { + try { + const { data } = await axios.post('http://localhost:5000/diffusion', { + prompt, + im_dataurl: dataURL, + }); + return data; + } catch (e) { + console.error('Failed to diffuse.'); + } +}; + +export const stableDiffusion = { diffusion }; diff --git a/client/src/components/lib/ContextMenu.tsx b/client/src/components/lib/ContextMenu.tsx index 4e208e3..2a4c752 100644 --- a/client/src/components/lib/ContextMenu.tsx +++ b/client/src/components/lib/ContextMenu.tsx @@ -5,6 +5,7 @@ import { useCanvasElementStore } from '@/stores/CanvasElementsStore'; import ExportSelectedPNGContextItem from './ExportSelectedPNGContextItem'; import ContextMenuItem from './ContextMenuItem'; import { useWebSocketStore } from '@/stores/WebSocketStore'; +import StableDiffusionContextItem from './StableDiffusion/StableDiffusionContextItem'; /** * Defines a context menu, with options, that is revealed @@ -55,6 +56,7 @@ const ContextMenu = () => { + ) : null} diff --git a/client/src/components/lib/StableDiffusion/StableDiffusionContextItem.tsx b/client/src/components/lib/StableDiffusion/StableDiffusionContextItem.tsx new file mode 100644 index 0000000..499d930 --- /dev/null +++ b/client/src/components/lib/StableDiffusion/StableDiffusionContextItem.tsx @@ -0,0 +1,30 @@ +import React from 'react'; +import { ImageIcon } from '@radix-ui/react-icons'; +import { useAppStore } from '@/stores/AppStore'; +import ContextMenuItem from '../ContextMenuItem'; + +/** + * Context Menu option that opens up the Stable Diffusion Sheet. + * @author Yousef Yassin + */ + +const StableDiffusionContextItem = () => { + const { setIsUsingStableDiffusion } = useAppStore([ + 'setIsUsingStableDiffusion', + ]); + return ( + { + setIsUsingStableDiffusion(true); + }} + > + Stable Diffusion +
+ +
+ + ); +}; + +export default StableDiffusionContextItem; diff --git a/client/src/components/lib/StableDiffusion/StableDiffusionSheet.tsx b/client/src/components/lib/StableDiffusion/StableDiffusionSheet.tsx new file mode 100644 index 0000000..4293f52 --- /dev/null +++ b/client/src/components/lib/StableDiffusion/StableDiffusionSheet.tsx @@ -0,0 +1,238 @@ +import React, { useEffect } from 'react'; +import { + Sheet, + SheetClose, + SheetContent, + SheetDescription, + SheetFooter, + SheetHeader, + SheetTitle, +} from '@/components/ui/sheet'; +import { Button } from '../../ui/button'; +import { Label } from '../../ui/label'; +import { Input } from '../../ui/input'; +import { useAppStore } from '@/stores/AppStore'; +import { useCanvasElementStore } from '@/stores/CanvasElementsStore'; +import { createElement } from '@/lib/canvasElements/canvasElementUtils'; +import { renderElementsOnOffscreenCanvas } from '@/lib/export'; +import { stableDiffusion } from '@/api'; +import { + dataURLToFile, + generateRandId, + getDataURL, + resizeImageFile, +} from '@/lib/bytes'; +import { injectImageElement } from '@/lib/image'; + +/** + * Sidebar sheet that allows the user to generate images using Stable Diffusion. + * @author Yousef Yassin + */ + +const StableDiffusionSheet = () => { + const { setPendingImageElement, addCanvasShape, editCanvasElement } = + useCanvasElementStore([ + 'setPendingImageElement', + 'addCanvasShape', + 'editCanvasElement', + ]); + const { isUsingStableDiffusion, setIsUsingStableDiffusion, zoom, appHeight } = + useAppStore([ + 'isUsingStableDiffusion', + 'setIsUsingStableDiffusion', + 'zoom', + 'appHeight', + ]); + const { canvasColor, setTool } = useAppStore(['canvasColor', 'setTool']); + const { + selectedElementIds, + p1, + p2, + types, + freehandPoints, + freehandBounds, + textStrings, + fontFamilies, + fontSizes, + fillColors, + fileIds, + isImagePlaceds, + angles, + roughElements, + opacities, + strokeColors, + strokeWidths, + } = useCanvasElementStore([ + 'selectedElementIds', + 'p1', + 'p2', + 'types', + 'freehandPoints', + 'freehandBounds', + 'textStrings', + 'fontFamilies', + 'fontSizes', + 'fillColors', + 'fileIds', + 'isImagePlaceds', + 'angles', + 'roughElements', + 'opacities', + 'strokeColors', + 'strokeWidths', + ]); + const [dataURL, setDataURL] = React.useState(''); + const [prompt, setPrompt] = React.useState(''); + const [diffusionImages, setDiffusionImages] = React.useState([]); + const [selectedIdx, setSelectedIdx] = React.useState(0); + const [isLoading, setIsLoading] = React.useState(false); + + const populateDataURL = () => { + const canvas = renderElementsOnOffscreenCanvas( + selectedElementIds, + { + p1, + p2, + angles, + types, + freehandPoints, + freehandBounds, + textStrings, + fontFamilies, + fontSizes, + fillColors, + isImagePlaceds, + fileIds, + roughElements, + opacities, + strokeColors, + strokeWidths, + }, + { + margin: 20, + canvasColor, + }, + ); + canvas && setDataURL(canvas.toDataURL('image/png')); + }; + + useEffect(() => { + populateDataURL(); + }, [isUsingStableDiffusion]); + return ( + + {/* Prevent closing when clicking outside */} + e.preventDefault()}> + + Stable Diffusion + + Enter a prompt, and watch the magic happen! + + +
+
+ +
+ + setPrompt(e.target.value)} + /> +
+
+
+ +
+
+ + {diffusionImages.length > 0 && ( +
+ {diffusionImages.map((imageDataURL, i) => ( +
+
setSelectedIdx(i)} + > + +
+
+ ))} +
+ )} + + + + + + + + + + ); +}; + +export default StableDiffusionSheet; diff --git a/client/src/components/ui/sheet.tsx b/client/src/components/ui/sheet.tsx new file mode 100644 index 0000000..a9dd568 --- /dev/null +++ b/client/src/components/ui/sheet.tsx @@ -0,0 +1,138 @@ +import * as React from 'react'; +import * as SheetPrimitive from '@radix-ui/react-dialog'; +import { cva, type VariantProps } from 'class-variance-authority'; +import { X } from 'lucide-react'; + +import { cn } from '@/lib/utils'; + +const Sheet = SheetPrimitive.Root; + +const SheetTrigger = SheetPrimitive.Trigger; + +const SheetClose = SheetPrimitive.Close; + +const SheetPortal = SheetPrimitive.Portal; + +const SheetOverlay = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + +)); +SheetOverlay.displayName = SheetPrimitive.Overlay.displayName; + +const sheetVariants = cva( + 'fixed z-50 gap-4 bg-background p-6 shadow-lg transition ease-in-out data-[state=open]:animate-in data-[state=closed]:animate-out data-[state=closed]:duration-300 data-[state=open]:duration-500', + { + variants: { + side: { + top: 'inset-x-0 top-0 border-b data-[state=closed]:slide-out-to-top data-[state=open]:slide-in-from-top', + bottom: + 'inset-x-0 bottom-0 border-t data-[state=closed]:slide-out-to-bottom data-[state=open]:slide-in-from-bottom', + left: 'inset-y-0 left-0 h-full w-3/4 border-r data-[state=closed]:slide-out-to-left data-[state=open]:slide-in-from-left sm:max-w-sm', + right: + 'inset-y-0 right-0 h-full w-3/4 border-l data-[state=closed]:slide-out-to-right data-[state=open]:slide-in-from-right sm:max-w-sm', + }, + }, + defaultVariants: { + side: 'right', + }, + }, +); + +interface SheetContentProps + extends React.ComponentPropsWithoutRef, + VariantProps {} + +const SheetContent = React.forwardRef< + React.ElementRef, + SheetContentProps +>(({ side = 'right', className, children, ...props }, ref) => ( + + + + {children} + + + Close + + + +)); +SheetContent.displayName = SheetPrimitive.Content.displayName; + +const SheetHeader = ({ + className, + ...props +}: React.HTMLAttributes) => ( +
+); +SheetHeader.displayName = 'SheetHeader'; + +const SheetFooter = ({ + className, + ...props +}: React.HTMLAttributes) => ( +
+); +SheetFooter.displayName = 'SheetFooter'; + +const SheetTitle = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + +)); +SheetTitle.displayName = SheetPrimitive.Title.displayName; + +const SheetDescription = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + +)); +SheetDescription.displayName = SheetPrimitive.Description.displayName; + +export { + Sheet, + SheetPortal, + SheetOverlay, + SheetTrigger, + SheetClose, + SheetContent, + SheetHeader, + SheetFooter, + SheetTitle, + SheetDescription, +}; diff --git a/client/src/hooks/useMultiSelection.tsx b/client/src/hooks/useMultiSelection.tsx index 7b762eb..94b43fb 100644 --- a/client/src/hooks/useMultiSelection.tsx +++ b/client/src/hooks/useMultiSelection.tsx @@ -1,3 +1,4 @@ +import { getOrientedBounds } from '@/lib/math'; import { CanvasElement, useCanvasElementStore, @@ -11,20 +12,21 @@ import { useEffect } from 'react'; */ const useMultiSelection = () => { - const { selectionFrame, setSelectedElements, allIds, p1, p2 } = + const { selectionFrame, setSelectedElements, allIds, p1, p2, angles } = useCanvasElementStore([ 'selectionFrame', 'setSelectedElements', 'allIds', 'p1', 'p2', + 'angles', ]); useEffect(() => { if (selectionFrame === null) return; const elementsWithinSelection = getElementsWithinFrame( - { elementIds: allIds, p1, p2 }, + { elementIds: allIds, p1, p2, angles }, selectionFrame, ); setSelectedElements(elementsWithinSelection); @@ -43,6 +45,7 @@ const getElementsWithinFrame = ( elementIds: string[]; p1: Record; p2: Record; + angles: Record; }, frame: { p1: CanvasElement['p1']; @@ -50,7 +53,7 @@ const getElementsWithinFrame = ( }, ) => { // Destructure properties from appState - const { elementIds, p1, p2 } = appState; + const { elementIds, p1, p2, angles } = appState; // Destructure coordinates of the frame const { x: frameX1, y: frameY1 } = frame.p1; @@ -58,11 +61,25 @@ const getElementsWithinFrame = ( // Filter element IDs based on whether their positions fall within the frame return elementIds.filter((id) => { - const { x: x1, y: y1 } = p1[id]; - const { x: x2, y: y2 } = p2[id]; + let { x: x1, y: y1 } = p1[id]; + let { x: x2, y: y2 } = p2[id]; + + const [cx, cy] = [(x1 + x2) / 2, (y1 + y2) / 2]; + ({ x1, y1, x2, y2 } = getOrientedBounds( + { x1, x2, y1, y2 }, + [cx, cy], + angles[id], + )); + + const minX = Math.min(x1, x2); + const maxX = Math.max(x1, x2); + const minY = Math.min(y1, y2); + const maxY = Math.max(y1, y2); // Check if the element is within the frame boundaries - return frameX1 <= x1 && frameY1 <= y1 && frameX2 >= x2 && frameY2 >= y2; + return ( + frameX1 <= minX && frameY1 <= minY && frameX2 >= maxX && frameY2 >= maxY + ); }); }; diff --git a/client/src/hooks/useShortcut.tsx b/client/src/hooks/useShortcut.tsx index 7f37c68..0e24154 100644 --- a/client/src/hooks/useShortcut.tsx +++ b/client/src/hooks/useShortcut.tsx @@ -117,6 +117,8 @@ export const useShortcuts = () => { }; const onWheel = (e: WheelEvent) => { + // Ignore wheel events not on canvas, for example, on a sheet. + if ((e.target as HTMLElement)?.id !== 'canvas') return; if (e.ctrlKey) { // Zoom event setAppZoom(clamp(zoom - e.deltaY * ZOOM.INC * 0.1, ZOOM.MIN, ZOOM.MAX)); diff --git a/client/src/hooks/webrtc/useRTCConsumer.tsx b/client/src/hooks/webrtc/useRTCConsumer.tsx index 45f12ba..4e2f31c 100644 --- a/client/src/hooks/webrtc/useRTCConsumer.tsx +++ b/client/src/hooks/webrtc/useRTCConsumer.tsx @@ -1,31 +1,15 @@ -import { REST, SECONDS_TO_MS, WS_TOPICS } from '@/constants'; +import { SECONDS_TO_MS, WS_TOPICS } from '@/constants'; import { createPeer, handleNegotiationNeededEvent } from '@/lib/webrtc'; import { useAuthStore } from '@/stores/AuthStore'; import { useWebSocketStore } from '@/stores/WebSocketStore'; -import axios from 'axios'; import { useEffect, useRef } from 'react'; +import { sfu } from '@/api'; /** * Hook that handles creating a consumer if a stream is initiated inside a room. * @author Yousef Yassin */ -/** - * Function to poll for an ongoing stream in a room and initialize a consumer if available. - * @param roomID String, the ID of the room to poll. - * @param initConsumer Function, callback to initialize the consumer when a stream is available. - */ -const pollOngoingStream = async (roomID: string, initConsumer: () => void) => { - try { - const { data } = await axios.put(REST.sfu.poll, { - roomId: roomID, - }); - data.roomHasProducer && initConsumer(); - } catch (e) { - console.error('Failed to poll for ongoing stream'); - } -}; - /** * Hook for managing the WebRTC consumer logic. * @param setScreenStream Function, callback to set the screen sharing stream. @@ -50,10 +34,7 @@ const useRTCConsumer = ( // On mount, check if there's a stream in the room. If so, initiate a consumer connection. // Give a second for socket to connect roomID && - setTimeout( - () => pollOngoingStream(roomID, initConsumer), - 1 * SECONDS_TO_MS, - ); + setTimeout(() => sfu.poll(roomID, initConsumer), 1 * SECONDS_TO_MS); }, [roomID]); // Cleanup on page refresh, close, or tab close diff --git a/client/src/stores/AppStore.ts b/client/src/stores/AppStore.ts index d6130d2..a1b0382 100644 --- a/client/src/stores/AppStore.ts +++ b/client/src/stores/AppStore.ts @@ -37,6 +37,7 @@ interface AppState { canvasColor: string; // Whether app is in transparent canvas mode. isTransparent: boolean; + isUsingStableDiffusion: boolean; } /** Reducers */ interface AppActions { @@ -52,6 +53,7 @@ interface AppActions { setIsInCall: (isInCall: boolean) => void; setCanvasBackground: (canvasColor: string) => void; setIsTransparent: (isTransparent: boolean) => void; + setIsUsingStableDiffusion: (isUsingStableDiffusion: boolean) => void; } type AppStore = AppState & AppActions; @@ -70,6 +72,7 @@ export const initialAppState: AppState = { panOffset: { x: 0, y: 0 }, canvasColor: '#fff', isTransparent: false, + isUsingStableDiffusion: false, }; /** Actions / Reducers */ @@ -112,6 +115,9 @@ const setPanOffset = (set: SetState) => (x: number, y: number) => const setCanvasBackground = (set: SetState) => (canvasColor: string) => set(() => ({ canvasColor })); +const setIsUsingStableDiffusion = + (set: SetState) => (isUsingStableDiffusion: boolean) => + set(() => ({ isUsingStableDiffusion })); /** Store Hook */ const appStore = create()((set) => ({ @@ -128,5 +134,6 @@ const appStore = create()((set) => ({ setIsInCall: setIsInCall(set), setCanvasBackground: setCanvasBackground(set), setIsTransparent: setIsTransparent(set), + setIsUsingStableDiffusion: setIsUsingStableDiffusion(set), })); export const useAppStore = createStoreWithSelectors(appStore); diff --git a/client/src/views/Viewport.tsx b/client/src/views/Viewport.tsx index 188fa71..7b045de 100644 --- a/client/src/views/Viewport.tsx +++ b/client/src/views/Viewport.tsx @@ -14,6 +14,7 @@ import ShareScreen from '@/components/lib/ShareScreen'; import ShareScreenButton from '@/components/lib/ShareScreenButton'; import TransparencyButton from '@/components/lib/TransparencyButton'; import { IS_ELECTRON_INSTANCE } from '@/constants'; +import StableDiffusionSheet from '@/components/lib/StableDiffusion/StableDiffusionSheet'; /** * Primary viewport that houses the canvas @@ -75,6 +76,7 @@ const Viewport = () => { +
diff --git a/sd/.gitignore b/sd/.gitignore new file mode 100644 index 0000000..6de30dd --- /dev/null +++ b/sd/.gitignore @@ -0,0 +1,4 @@ +venv/ +__pycache__/ +assets/ +*.ipynb \ No newline at end of file diff --git a/sd/Dockerfile b/sd/Dockerfile new file mode 100644 index 0000000..39c7283 --- /dev/null +++ b/sd/Dockerfile @@ -0,0 +1,18 @@ +# Using lightweight alpine image +FROM python:3.8-alpine + +# Installing packages +RUN apk update +RUN pip install --no-cache-dir pipenv + +# Defining working directory and adding source code +WORKDIR /usr/src/app +COPY Pipfile Pipfile.lock bootstrap.sh ./ +COPY cashman ./cashman + +# Install API dependencies +RUN pipenv install --system --deploy + +# Start app +EXPOSE 5000 +ENTRYPOINT ["/usr/src/app/bootstrap.sh"] \ No newline at end of file diff --git a/sd/Pipfile b/sd/Pipfile new file mode 100644 index 0000000..5750825 --- /dev/null +++ b/sd/Pipfile @@ -0,0 +1,38 @@ +[[source]] +url = "https://pypi.org/simple" +verify_ssl = true +name = "pypi" + +[[source]] +url = "https://download.pytorch.org/whl/cu118" +verify_ssl = true +name = "downloadpytorch" + +[[source]] +url = "https://download.pytorch.org/whl/cu118" +verify_ssl = true +name = "downloadpytorch" + +[[source]] +url = "https://download.pytorch.org/whl/cu118" +verify_ssl = true +name = "downloadpytorch" + +[packages] +flask = "*" +marshmallow = "*" +diffusers = "*" +transformers = "*" +accelerate = "*" +peft = "*" +gradio = "==3.50.2" +torch = {version = "==2.0.1", index = "downloadpytorch"} +torchvision = {version = "*", index = "downloadpytorch"} +torchaudio = {version = "*", index = "downloadpytorch"} +flask-cors = "*" + +[dev-packages] + +[requires] +python_version = "3.11" +python_full_version = "3.11.4" diff --git a/sd/Pipfile.lock b/sd/Pipfile.lock new file mode 100644 index 0000000..32aead0 --- /dev/null +++ b/sd/Pipfile.lock @@ -0,0 +1,1830 @@ +{ + "_meta": { + "hash": { + "sha256": "e3b6394b7b8316461a576680337bbea175c66e09b6ff0569544c19faf34c55d4" + }, + 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"python_version >= '3.8'", + "version": "==3.17.0" + } + }, + "develop": {} +} diff --git a/sd/bootstrap.sh b/sd/bootstrap.sh new file mode 100644 index 0000000..0e162bf --- /dev/null +++ b/sd/bootstrap.sh @@ -0,0 +1,3 @@ +#!/bin/sh +export FLASK_APP=./src/index.py +pipenv run flask --debug run -h 0.0.0.0 diff --git a/sd/src/__init__.py b/sd/src/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/sd/src/index.py b/sd/src/index.py new file mode 100644 index 0000000..f113bad --- /dev/null +++ b/sd/src/index.py @@ -0,0 +1,61 @@ +from flask import Flask, request, jsonify +from flask_cors import CORS + +from .util.bytes import pil_image_to_data_url, data_url_to_pil_image +from .util.pipeline import DiffuserPipeline +from .models.SDRequest import SDRequestSchema + +""" +Defines a Flask web application that exposes two endpoints: +1. /test: Returns a simple "Online" message to check if the server is running. +2. /diffusion: Accepts a POST request with JSON data containing an image data URL and a prompt. + It uses a DiffuserPipeline to generate a series of diffused images based on the provided data. + It returns a JSON response containing a list of image data URLs. +@author Yousef Yassin +""" + +# Initializing the Flask app +app = Flask(__name__) +# Enabling CORS for the app +CORS(app) + +# Creating an instance of DiffuserPipeline with a specific model +pipeline = DiffuserPipeline(model_name="stable_diffusion_14") + + +# Endpoint to check if the server is online +@app.route("/test") +def get_test(): + return "Online" + + +# Endpoint to perform image diffusion based on received image and prompt +@app.route("/diffusion", methods=["POST"]) +def post_diffusion(): + sd_request = SDRequestSchema().load(request.get_json()) + # Converting the image data URL in the request to a PIL image + # TODO: TEST THIS IS CORRECT + init_image = data_url_to_pil_image(data_url=sd_request["im_dataurl"]) + # Generating a series of images using the DiffuserPipeline + images = pipeline.generate_images( + prompt=sd_request["prompt"], + init_image=init_image, + num_images=5, + # TODO: These will be passed in req + num_inference_steps=40, + strength=0.5, + guidance_scale=7.5, + # lcm_origin_steps=50, + # strength=0.8, + ) + # TODO: Use generator if more images / diff size + # Converting the generated images to data URLs + image_data_urls = [pil_image_to_data_url(image) for image in images] + # Creating a JSON response with the generated image data URLs + response = jsonify({"image_data_urls": image_data_urls}) + # Returning the JSON response + return response + + +if __name__ == "__main__": + app.run(debug=True) diff --git a/sd/src/models/SDRequest.py b/sd/src/models/SDRequest.py new file mode 100644 index 0000000..865d165 --- /dev/null +++ b/sd/src/models/SDRequest.py @@ -0,0 +1,56 @@ +from marshmallow import Schema, fields + +""" +Defines a data class (SDRequest) representing a request for image diffusion and a schema class +(SDRequestSchema) for validating and deserializing JSON data into SDRequest objects. +@author Yousef Yassin +""" + + +class SDRequest(object): + """ + Class representing a request for image diffusion. + + Attributes: + im_dataurl (str): Image data URL for the initial image. + prompt (str): Prompt for generating diffused images. + + Methods: + __init__(self, im_dataurl, prompt): Initializes SDRequest with image data URL and prompt. + __repr__(self): Returns a string representation of the SDRequest object. + + """ + + def __init__(self, im_dataurl, prompt): + """ + Initializes SDRequest with image data URL and prompt. + + Args: + im_dataurl (str): Image data URL for the initial image. + prompt (str): Prompt for generating diffused images. + """ + self.im_dataurl = im_dataurl + self.prompt = prompt + + def __repr__(self): + """ + Returns a string representation of the SDRequest object. + + Returns: + str: String representation of the SDRequest object. + """ + return "".format(self=self) + + +class SDRequestSchema(Schema): + """ + Schema class for validating and deserializing JSON data into SDRequest objects. + + Fields: + im_dataurl (fields.Str): String field for image data URL. + prompt (fields.Str): String field for the prompt. + + """ + + im_dataurl = fields.Str() + prompt = fields.Str() diff --git a/sd/src/models/__init__.py b/sd/src/models/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/sd/src/util/bytes.py b/sd/src/util/bytes.py new file mode 100644 index 0000000..34f4530 --- /dev/null +++ b/sd/src/util/bytes.py @@ -0,0 +1,65 @@ +from PIL import Image +import base64 +from io import BytesIO + +""" +Defines byte-level operations for encoding and decoding images. +@author Yousef Yassin +""" + + +def pil_image_to_data_url(pil_image: Image.Image, format: str = "PNG") -> str: + """ + Convert the specified PIL image to a data URL. + + Args: + pil_image (Image.Image): The PIL image to convert. + format (str): The image format (defaults to "PNG"). + + Returns: + str: The data URL representing the image. + """ + # Convert PIL image to bytes + image_stream = BytesIO() + pil_image.save(image_stream, format=format) + image_data = image_stream.getvalue() + + # Encode the image data in base64 + base64_encoded = base64.b64encode(image_data).decode("utf-8") + + # Create the data URL + data_url = f"data:image/{format.lower()};base64,{base64_encoded}" + return data_url + + +# B64 padding +PADDING_MULTIPLE = 4 + + +def data_url_to_pil_image(data_url: str) -> Image.Image: + """ + Convert a data URL to a PIL image. + + Args: + data_url (str): The data URL representing the image. + + Returns: + Image.Image: The PIL image. + """ + # Extract the base64-encoded image data from the data URL + _, data = data_url.split(",", 1) + + # Add padding if necessary + # Source: An additional pad character is allocated which may + # be used to force the encoded output into an integer multiple of 4 characters + padding = "=" * (PADDING_MULTIPLE - len(data) % PADDING_MULTIPLE) + data += padding + + # Decode base64 and create BytesIO object + image_data = base64.b64decode(data) + image_stream = BytesIO(image_data) + + # Load PIL image + pil_image = Image.open(image_stream) + + return pil_image diff --git a/sd/src/util/pipeline.py b/sd/src/util/pipeline.py new file mode 100644 index 0000000..ba3ce4e --- /dev/null +++ b/sd/src/util/pipeline.py @@ -0,0 +1,99 @@ +import torch +from diffusers import DiffusionPipeline, StableDiffusionImg2ImgPipeline + +""" +Defines utility functions for loading pre-trained diffusion models and a class +(DiffuserPipeline) for generating diffused images using the loaded models. +@author Yousef Yassin +""" + + +def load_model(model_name: str): + """ + Load a pre-trained diffusion model based on the specified model_name. + + Args: + model_name (str): Name of the diffusion model. + + Returns: + diffusers.DiffusionPipeline or diffusers.StableDiffusionImg2ImgPipeline: Loaded model instance. + """ + match model_name: + case "dreamshaper": + # Loading Dreamshaper model + pipeline = DiffusionPipeline.from_pretrained( + "SimianLuo/LCM_Dreamshaper_v7", + revision="fb9c5d167af11fd84454ae6493878b10bb63b067", + safety_checker=None, + custom_pipeline="latent_consistency_img2img", + ) + pipeline.to(torch_device="cuda", torch_dtype=torch.float16) + pipeline.set_progress_bar_config(disable=True) + return pipeline + + case "stable_diffusion_14": + # Loading Stable Diffusion model version 1.4 + pipeline = StableDiffusionImg2ImgPipeline.from_pretrained( + "CompVis/stable-diffusion-v1-4", + revision="fp16", + torch_dtype=torch.float16, + use_auth_token=True, + ) + pipeline.to(torch_device="cuda", torch_dtype=torch.float16) + pipeline.set_progress_bar_config(disable=True) + return pipeline + + +class DiffuserPipeline: + """ + Wrapper class for a diffusion model with pre-trained weights, providing an interface for generating diffused images. + + Attributes: + pipeline: An instance of a pre-trained diffusion model. + + Methods: + __init__(self, model_name: str): Initializes DiffuserPipeline with the specified model_name. + load_model(self, model_name: str): Loads a pre-trained diffusion model based on the model_name. + generate_images(self, prompt: str, init_image, num_images: int = 5, **kwargs): Generates a series of diffused images. + """ + + def __init__(self, model_name: str): + """ + Initialize DiffuserPipeline with the specified model_name. + + Args: + model_name (str): Name of the diffusion model. + """ + self.load_model(model_name=model_name) + + def load_model(self, model_name: str): + """ + Load a pre-trained diffusion model based on the specified model_name. + + Args: + model_name (str): Name of the diffusion model. + """ + self.pipeline = load_model(model_name=model_name) + + def generate_images(self, prompt: str, init_image, num_images: int = 5, **kwargs): + """ + Generate a series of diffused images based on a prompt. + + Args: + prompt (str): Prompt for generating images. + init_image: Initial image for the diffusion process. + num_images (int): Number of images to generate. + **kwargs: Additional arguments to pass to the diffusion model. + + Returns: + list: List of generated diffused images. + """ + images = [] + for _ in range(num_images): + # TODO: Add negative prompr, guidance, scale on gui + # image = pipeline(prompt, negative_prompt=negative_prompt, image=init_image).images[0] + # Generating diffused image using the loaded model + image = self.pipeline(prompt, image=init_image, **kwargs).images[0] + images.append(image) + + return images