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README.md
Imgae matting
Here are a few effects(omitting mask images):
How to Run
Method 1: Run from Source Code
Firstly, you need to download the project code and install the required dependencies.
# Python 3.10
git clone https://github.com/ihmily/image-matting.git
cd image-matting
pip install -r requirements.txt
Next, use the following command to run the web interface.
python app.py
Finally, visit http://127.0.0.1:8000/.
Method 2: Run with Docker
Simply run the following commands after entering the project folder.
Pull the Docker image.
docker pull ihmily/image-matting:latest
After the image is pulled, run the container.
docker run -p 8000:8000 ihmily/image-matting:latest
Alternatively, you can build the image yourself.
docker build -t image-matting:latest .
docker run -p 8000:8000 image-matting:latest
Lastly, visit http://127.0.0.1:8000 to perform online image matting. Feel free to choose the method that suits your preference.
Use API
Please run it before use API
File upload
import requests
server = "http://127.0.0.1:8000"
image_path = "image.png"
model_name = "universal" # people,universal
files = {"image": (image_path, open(image_path, "rb"))}
data = {"model": model_name}
response = requests.post(server+'/matting', files=files, data=data)
print(response.text)
json_data = response.json()
image_url = json_data['result_image_url']
mask_url = json_data['mask_image_url']
print("image_url:", server + image_url)
print("mask_url:", server + mask_url)
Url upload
import requests
server = "http://127.0.0.1:8000"
image_url = "http://your-image-url/demo.png"
data = {"image_url": image_url, "model": "universal"} # people,universal
response = requests.post(server+'/matting/url', json=data)
print(response.text)
json_data = response.json()
image_url = json_data['result_image_url']
mask_url = json_data['mask_image_url']
print("image_url:",server+image_url)
print("mask_url:",server+mask_url)
You can freely choose the method you want to upload from above.If you want to get the cropped cutout, you can call crop_image_by_alpha_channel
function.
Extended Gallery
References
https://modelscope.cn/models/damo/cv_unet_universal-matting/summary
https://modelscope.cn/models/damo/cv_unet_image-matting/summary