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@ -4,9 +4,8 @@ import sys
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import os
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import os
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import uuid
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import uuid
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from datetime import datetime
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from datetime import datetime
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from fastapi import FastAPI, File, UploadFile, Form, HTTPException
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import httpx
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from fastapi import Request
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from fastapi import FastAPI, File, UploadFile, Form, HTTPException, Request, status
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import requests
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import cv2
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import cv2
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from modelscope.pipelines import pipeline
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from modelscope.pipelines import pipeline
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from modelscope.utils.constant import Tasks
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from modelscope.utils.constant import Tasks
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@ -40,6 +39,8 @@ class ModelLoader:
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def load_model(self, model_name):
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def load_model(self, model_name):
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if model_name not in self.loaded_models:
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if model_name not in self.loaded_models:
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model_info = model_paths[model_name]
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model_info = model_paths[model_name]
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if not model_info:
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raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="Invalid model selection")
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model_path = model_info['path']
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model_path = model_info['path']
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task_group = model_info['task']
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task_group = model_info['task']
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@ -50,6 +51,14 @@ class ModelLoader:
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model_loader = ModelLoader()
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model_loader = ModelLoader()
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def get_filename():
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filename = uuid.uuid4()
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original_image_filename = f"original_{filename}.png"
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image_filename = f"image_{filename}.png"
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mask_filename = f"mask_{filename}.png"
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return original_image_filename, image_filename, mask_filename
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# remove excess transparent background and crop the image
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# remove excess transparent background and crop the image
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def crop_image_by_alpha_channel(input_image: np.ndarray | str, output_path: str):
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def crop_image_by_alpha_channel(input_image: np.ndarray | str, output_path: str):
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img_array = cv2.imread(input_image, cv2.IMREAD_UNCHANGED) if isinstance(input_image, str) else input_image
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img_array = cv2.imread(input_image, cv2.IMREAD_UNCHANGED) if isinstance(input_image, str) else input_image
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@ -62,49 +71,90 @@ def crop_image_by_alpha_channel(input_image: np.ndarray | str, output_path: str)
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cropped_img_array = img_array[y:y + h, x:x + w]
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cropped_img_array = img_array[y:y + h, x:x + w]
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cv2.imwrite(output_path, cropped_img_array)
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cv2.imwrite(output_path, cropped_img_array)
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return output_path
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return output_path
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@app.post("/switch_model/{new_model}")
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async def switch_model(new_model: str):
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if new_model not in model_paths:
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return {"content": "Invalid model selection"}, 400
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model_info = model_paths[new_model]
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loaded_models[new_model] = pipeline(model_info['task'], model=model_info['path'])
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def process_image(image_bytes: bytes):
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model_loader.loaded_models = loaded_models
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img = cv2.imdecode(np.frombuffer(image_bytes, np.uint8), cv2.IMREAD_UNCHANGED)
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return {"content": f"Switched to model: {new_model}"}, 200
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final_img = convert_image_to_white_background(image=img)
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if final_img is None:
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raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="Invalid image")
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return final_img
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@app.post("/matting")
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def convert_image_to_white_background(image_path: str = None, image: np.ndarray | None = None):
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async def matting(image: UploadFile = File(...), model: str = Form(default=default_model, alias="model")):
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try:
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image_bytes = await image.read()
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if image_path is not None:
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img = cv2.imdecode(np.frombuffer(image_bytes, np.uint8), cv2.IMREAD_COLOR)
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img = cv2.imread(image_path, cv2.IMREAD_UNCHANGED)
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elif image is not None:
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img = image
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else:
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raise ValueError("Either image_path or image must be provided.")
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if model not in model_paths:
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if img.shape[2] == 4:
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return {"content": "Invalid model selection"}, 400
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alpha_channel = img[:, :, 3]
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rgb_channels = img[:, :, :3]
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selected_model = model_loader.load_model(model)
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alpha_channel_3d = alpha_channel[:, :, np.newaxis] / 255.0
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alpha_channel_3d = np.repeat(alpha_channel_3d, 3, axis=2)
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filename = uuid.uuid4()
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white_background_image = np.ones_like(rgb_channels, dtype=np.uint8) * 255
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original_image_filename = f"original_{filename}.png"
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image_filename = f"image_{filename}.png"
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mask_filename = f"mask_{filename}.png"
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cv2.imwrite(os.path.join(UPLOAD_FOLDER, original_image_filename), img)
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foreground = cv2.multiply(rgb_channels, alpha_channel_3d, dtype=cv2.CV_8UC3)
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background = cv2.multiply(white_background_image, 1 - alpha_channel_3d, dtype=cv2.CV_8UC3)
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result = selected_model(img)
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final_img = cv2.add(foreground, background)
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else:
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final_img = img
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return final_img
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except Exception as e:
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print(f'Error: {e}')
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return None
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cv2.imwrite(os.path.join(OUTPUT_FOLDER, image_filename), result[OutputKeys.OUTPUT_IMG])
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cv2.imwrite(os.path.join(OUTPUT_FOLDER, mask_filename), result[OutputKeys.OUTPUT_IMG][:, :, 3])
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response_data = {
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@app.post("/switch_model/{new_model}")
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"result_image_url": f"/output/{image_filename}",
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async def switch_model(new_model: str):
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"mask_image_url": f"/output/{mask_filename}",
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if new_model not in model_paths:
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"original_image_size": {"width": img.shape[1], "height": img.shape[0]},
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return {"content": "Invalid model selection"}, status.HTTP_400_BAD_REQUEST
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"generation_time": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
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model_info = model_paths[new_model]
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}
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return response_data
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loaded_models[new_model] = pipeline(model_info['task'], model=model_info['path'])
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model_loader.loaded_models = loaded_models
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return {"content": f"Switched to model: {new_model}"}, status.HTTP_200_OK
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@app.post("/matting")
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async def matting(image: UploadFile = File(...), model: str = Form(default=default_model, alias="model")):
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try:
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image_bytes = await image.read()
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img = cv2.imdecode(np.frombuffer(image_bytes, np.uint8), cv2.IMREAD_UNCHANGED)
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if model not in model_paths:
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return {"content": "Invalid model selection"}, status.HTTP_400_BAD_REQUEST
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selected_model = model_loader.load_model(model)
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original_image_filename, image_filename, mask_filename = get_filename()
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cv2.imwrite(os.path.join(UPLOAD_FOLDER, original_image_filename), img)
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final_img = convert_image_to_white_background(image=img)
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if final_img is None:
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raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="Invalid image")
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result = selected_model(final_img)
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cv2.imwrite(os.path.join(OUTPUT_FOLDER, image_filename), result[OutputKeys.OUTPUT_IMG])
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cv2.imwrite(os.path.join(OUTPUT_FOLDER, mask_filename), result[OutputKeys.OUTPUT_IMG][:, :, 3])
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response_data = {
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"code": 0,
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"result_image_url": f"/output/{image_filename}",
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"mask_image_url": f"/output/{mask_filename}",
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"original_image_size": {"width": img.shape[1], "height": img.shape[0]},
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"generation_time": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
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}
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return response_data
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except HTTPException as e:
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return {"error": str(e)}, e.status_code
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except Exception as e:
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return {"error": str(e)}, status.HTTP_500_INTERNAL_SERVER_ERROR
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@app.post("/matting/url")
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@app.post("/matting/url")
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@ -113,37 +163,37 @@ async def matting_url(request: Request, model: str = Form(default=default_model,
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json_data = await request.json()
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json_data = await request.json()
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image_url = json_data.get("image_url")
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image_url = json_data.get("image_url")
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except Exception as e:
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except Exception as e:
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raise HTTPException(status_code=400, detail=f"Error parsing JSON data: {str(e)}")
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raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=f"Error parsing JSON data: {str(e)}")
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if not image_url:
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if not image_url:
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raise HTTPException(status_code=400, detail="Image URL is required")
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raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="Image URL is required")
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try:
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try:
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response = requests.get(image_url)
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async with httpx.AsyncClient() as client:
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response.raise_for_status()
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response = await client.get(image_url)
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img_array = np.frombuffer(response.content, dtype=np.uint8)
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response.raise_for_status()
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img = cv2.imdecode(img_array, cv2.IMREAD_COLOR)
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img_array = np.frombuffer(response.content, dtype=np.uint8)
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except requests.RequestException as e:
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img = cv2.imdecode(img_array, cv2.IMREAD_UNCHANGED)
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raise HTTPException(status_code=400, detail=f"Failed to fetch image from URL: {str(e)}")
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except httpx.RequestError as e:
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raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=f"Failed to fetch image from URL: {str(e)}")
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if model not in model_paths:
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if model not in model_paths:
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raise HTTPException(status_code=400, detail="Invalid model selection")
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raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="Invalid model selection")
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selected_model = model_loader.load_model(model)
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selected_model = model_loader.load_model(model)
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original_image_filename, image_filename, mask_filename = get_filename()
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filename = uuid.uuid4()
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original_image_filename = f"original_{filename}.png"
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image_filename = f"image_{filename}.png"
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mask_filename = f"mask_{filename}.png"
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cv2.imwrite(os.path.join(UPLOAD_FOLDER, original_image_filename), img)
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cv2.imwrite(os.path.join(UPLOAD_FOLDER, original_image_filename), img)
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result = selected_model(img)
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final_img = convert_image_to_white_background(image=img)
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if final_img is None:
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raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="Invalid image")
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result = selected_model(final_img)
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cv2.imwrite(os.path.join(OUTPUT_FOLDER, image_filename), result[OutputKeys.OUTPUT_IMG])
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cv2.imwrite(os.path.join(OUTPUT_FOLDER, image_filename), result[OutputKeys.OUTPUT_IMG])
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cv2.imwrite(os.path.join(OUTPUT_FOLDER, mask_filename), result[OutputKeys.OUTPUT_IMG][:, :, 3])
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cv2.imwrite(os.path.join(OUTPUT_FOLDER, mask_filename), result[OutputKeys.OUTPUT_IMG][:, :, 3])
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response_data = {
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response_data = {
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"code": 0,
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"result_image_url": f"/output/{image_filename}",
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"result_image_url": f"/output/{image_filename}",
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"mask_image_url": f"/output/{mask_filename}",
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"mask_image_url": f"/output/{mask_filename}",
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"original_image_size": {"width": img.shape[1], "height": img.shape[0]},
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"original_image_size": {"width": img.shape[1], "height": img.shape[0]},
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@ -161,12 +211,16 @@ app.mount("/upload", StaticFiles(directory="./upload"), name="upload")
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@app.get("/")
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@app.get("/")
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async def read_index(request: Request):
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async def read_index(request: Request):
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return templates.TemplateResponse("index.html", {"request": request, "default_model": default_model,
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return templates.TemplateResponse(
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"available_models": list(model_paths.keys())})
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"index.html", {
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"request": request,
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"default_model": default_model,
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"available_models": list(model_paths.keys())
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})
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if __name__ == "__main__":
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if __name__ == "__main__":
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import uvicorn
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import uvicorn
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defult_bind_host = "0.0.0.0" if sys.platform != "win32" else "127.0.0.1"
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default_bind_host = "0.0.0.0" if sys.platform != "win32" else "127.0.0.1"
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uvicorn.run(app, host=defult_bind_host, port=8000)
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uvicorn.run(app, host=default_bind_host, port=8000)
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