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image_matting
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Fix transparent background image cutout

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ihmily 8 months ago
parent b0062b7a32
commit 419c8c1120
1 changed files with 108 additions and 54 deletions
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162
app.py
Unescape Escape View File

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

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