YoDe-Segmentation

Usage

Step 1: Environ building

git clone https://github.com/OneChorm/YoDe-Segmentation
conda create -n YoDe_Seg python==3.10.11
conda activate YoDe_Seg
pip install torch==1.11.0+cu113 torchvision==0.12.0+cu113 torchaudio==0.11.0 --extra-index-url https://download.pytorch.org/whl/cu113
cd "your dir to `YoDe-Segmentation`" # change directory
pip install -r requirements.txt
pip install YoDe-Segmentation-v2==1.0.1

Step 2: Weight configuration

Put the weight of Deeplabv3 model and the weight of YOLOV5 model in the weights folder

Step 3: Where should you put the images you want to predict

If you need to work with pdf files, you should put the files in the test_pdf folder,and then convert pdf files to images. If you run into an error with the pdf conversion, you could run the pdf2img.py in a python compiler.

run the pdf2img.py

python pdf2img.py

if need to work with images, you should only put the images in the test_img folder

Step 4: Predict

run the predict_molecular.py

python predict_molecular.py

Example

More examples are given in this Jupyter Notebook.

Datasets

You can download the Datasets at YoDe-Segmentation_data