https://github.com/abhishtagatya/backsub-cv

🌇 Background Substitution using Classical Method
https://github.com/abhishtagatya/backsub-cv

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🌇 Background Substitution using Classical Method

• Host: GitHub
• URL: https://github.com/abhishtagatya/backsub-cv
• Owner: abhishtagatya
• Created: 2024-04-11T18:34:51.000Z (7 months ago)
• Default Branch: master
• Last Pushed: 2024-04-28T12:08:39.000Z (7 months ago)
• Last Synced: 2024-05-08T00:12:28.057Z (6 months ago)
• Language: Python
• Size: 764 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# BackSub CV

> Background Substitution using Python's OpenCV

![Background Substitution](docs/GradientMixing.png)

### Quick Usage

Install requirements.

```shell

pip install -r requirements.txt

```

Experimentation may include the use of your own dataset. For verification, use the [Supervisely Segmentation Sample Dataset](https://drive.google.com/file/d/1biTZkShX_LxtIuuEKTV_mbyuUd-23oD6/view?usp=sharing)

and the [WikiArt Dataset](https://www.kaggle.com/datasets/ikarus777/best-artworks-of-all-time).

#### Run Single Task

Run Single Backgorund Substitution Task on an Image and a desired Backgorund

```shell

python3 run.py    --blend_mode=

```

- model : Model of Image Segmentation ('contourmask', 'grabcut', 'watershed')

- image_file : Path to Image File (image.png)

- background_file : Path to Substitute Background File (background.png)

- (Optional) blend_mode : Image Blending Mode ( "gradient_mix", "balance", "hist_match_s", "hist_match_t", "none")

- (Optional) file_out : Output File (result.png)

#### Run Evaluation of Model

Run an evaluation of the model for IoU and Pixel Accuracy metric

```shell

python3 run.py    

```

- model : Model of Image Segmentation ('contourmask', 'grabcut', 'watershed')

- image_path : Path to Images (images/)

- mask_path : Path to Ground Truth Masks (masks/)

- backgorund_file : Path to Substitute Background (background.png)