https://github.com/rizwanmunawar/yolov7-segmentation
YOLOv7 Instance Segmentation using OpenCV and PyTorch
https://github.com/rizwanmunawar/yolov7-segmentation
imagesegmentation medium-article opencv-python yolov5 yolov7-mask
Last synced: about 1 month ago
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YOLOv7 Instance Segmentation using OpenCV and PyTorch
- Host: GitHub
- URL: https://github.com/rizwanmunawar/yolov7-segmentation
- Owner: RizwanMunawar
- License: gpl-3.0
- Created: 2022-08-19T13:23:09.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2025-04-29T13:06:07.000Z (about 2 months ago)
- Last Synced: 2025-04-29T14:27:30.596Z (about 2 months ago)
- Topics: imagesegmentation, medium-article, opencv-python, yolov5, yolov7-mask
- Language: Python
- Homepage:
- Size: 4.9 MB
- Stars: 327
- Watchers: 2
- Forks: 78
- Open Issues: 19
-
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
- License: LICENSE
Awesome Lists containing this project
README
# YOLOv7 Instance Segmentation
🚀 [Read the blog](https://muhammadrizwanmunawar.medium.com/train-yolov7-segmentation-on-custom-data-b91237bd2a29)
## Steps to run Code
- Clone the repository
```bash
git clone https://github.com/RizwanMunawar/yolov7-segmentation.git
```
- Goto the cloned folder.
```bash
cd yolov7-segmentation
```
- Create a virtual envirnoment (Recommended, If you dont want to disturb python packages)
```bash
### For Linux Users
python3 -m venv yolov7seg
source yolov7seg/bin/activate
### For Window Users
python3 -m venv yolov7seg
cd yolov7seg
cd Scripts
activate
cd ..
cd ..
```
- Upgrade pip with mentioned command below.
```bash
pip install --upgrade pip
```
- Install requirements with mentioned command below.
```bash
pip install -r requirements.txt
```
- Download weights from [link](https://github.com/RizwanMunawar/yolov7-segmentation/releases/download/yolov7-segmentation/yolov7-seg.pt) and store in "yolov7-segmentation" directory.
- Run the code with mentioned command below.
```bash
#for segmentation with detection
python3 segment/predict.py --weights yolov7-seg.pt --source "videopath.mp4"
#for segmentation with detection + Tracking
python3 segment/predict.py --weights yolov7-seg.pt --source "videopath.mp4" --trk
#save the labels files of segmentation
python3 segment/predict.py --weights yolov7-seg.pt --source "videopath.mp4" --save-txt
```
- Output file will be created in the working directory with name `yolov7-segmentation/runs/predict-seg/exp/original-video-name.mp4`
### RESULTS
Car Semantic Segmentation
Car Semantic Segmentation
Person Segmentation + Tracking
### Custom Data Labelling
- I have used [roboflow](https://roboflow.com/) for data labelling. The data labelling for Segmentation will be a Polygon box,While data labelling for object detection will be a bounding box
- Go to the [link](https://app.roboflow.com/my-personal-workspace/createSample) and create a new workspace. Make sure to login with roboflow account.
- Once you will click on create workspace, You will see the popup as shown below to upload the dataset.
- Click on upload dataset and roboflow will ask for workspace name as shown below. Fill that form and then click on Create Private Project
- Note: Make sure to select Instance Segmentation Option in below image.
-You can upload your dataset now.
- Once files will upload, you can click on Finish Uploading.
- Roboflow will ask you to assign Images to someone, click on Assign Images.
- After that, you will see the tab shown below.
- Click on any Image in Unannotated tab, and then you can start labelling.
- Note: Press p and then draw polygon points for segmentation
- Once you will complete labelling, you can then export the data and follow mentioned steps below to start training.
### Custom Training
- Move your (segmentation custom labelled data) inside "yolov7-segmentation\data" folder by following mentioned structure.
- Go to the data folder, create a file with name custom.yaml and paste the mentioned code below inside that.
```yaml
train: "path to train folder"
val: "path to validation folder"
# number of classes
nc: 1
# class names
names: [ 'car']
```
- Download weights from the link and move to yolov7-segmentation folder.
- Go to the terminal, and run mentioned command below to start training.
```bash
python3 segment/train.py --data data/custom.yaml \
--batch 4 \
--weights "yolov7-seg.pt"
--cfg yolov7-seg.yaml \
--epochs 10 \
--name yolov7-seg \
--img 640 \
--hyp hyp.scratch-high.yaml
```
### Custom Model Detection Command
```bash
python3 segment/predict.py --weights "runs/yolov7-seg/exp/weights/best.pt" --source "videopath.mp4"
```
### RESULTS
Car Semantic Segmentation
Car Semantic Segmentation
Person Segmentation + Tracking
### References
- https://github.com/WongKinYiu/yolov7/tree/u7/seg
- https://github.com/ultralytics/yolov5
**Some of my articles/research papers | computer vision awesome resources for learning | How do I appear to the world? 🚀**
[Ultralytics YOLO11: Object Detection and Instance Segmentation🤯](https://muhammadrizwanmunawar.medium.com/ultralytics-yolo11-object-detection-and-instance-segmentation-88ef0239a811) 
[Parking Management using Ultralytics YOLO11](https://muhammadrizwanmunawar.medium.com/parking-management-using-ultralytics-yolo11-fba4c6bc62bc) 
[My 🖐️Computer Vision Hobby Projects that Yielded Earnings](https://muhammadrizwanmunawar.medium.com/my-️computer-vision-hobby-projects-that-yielded-earnings-7923c9b9eead) 
[Best Resources to Learn Computer Vision](https://muhammadrizwanmunawar.medium.com/best-resources-to-learn-computer-vision-311352ed0833) 
[Roadmap for Computer Vision Engineer](https://medium.com/augmented-startups/roadmap-for-computer-vision-engineer-45167b94518c) 
[How did I spend 2022 in the Computer Vision Field](https://www.linkedin.com/pulse/how-did-i-spend-2022-computer-vision-field-muhammad-rizwan-munawar) 
[Domain Feature Mapping with YOLOv7 for Automated Edge-Based Pallet Racking Inspections](https://www.mdpi.com/1424-8220/22/18/6927) 
[Exudate Regeneration for Automated Exudate Detection in Retinal Fundus Images](https://ieeexplore.ieee.org/document/9885192) 
[Feature Mapping for Rice Leaf Defect Detection Based on a Custom Convolutional Architecture](https://www.mdpi.com/2304-8158/11/23/3914) 
[Yolov5, Yolo-x, Yolo-r, Yolov7 Performance Comparison: A Survey](https://aircconline.com/csit/papers/vol12/csit121602.pdf) 
[Explainable AI in Drug Sensitivity Prediction on Cancer Cell Lines](https://ieeexplore.ieee.org/document/9922931) 
[Train YOLOv8 on Custom Data](https://medium.com/augmented-startups/train-yolov8-on-custom-data-6d28cd348262) 
**More Information**
For more details, you can reach out to me on [Medium](https://muhammadrizwanmunawar.medium.com/) or can connect with me on [LinkedIn](https://www.linkedin.com/in/muhammadrizwanmunawar/)