Metadata-Version: 2.1
Name: samclipdiffusion
Version: 0.0.3b0
Summary: A package for clip-guided diffusion
Home-page: https://github.com/eren23/sam-clip-diffusion
Author: Eren Akbulut
Author-email: erenakbulutwork@gmail.com
License: UNKNOWN
Description: # SAM + CLIP + DIFFUSION
        
        Stuff about this pipeline was a bit harder to run and follow, I wanted to write a simple package to allow people to use it with a higher level of abstraction. Based on the repos on the citation part.
        
        <div style="display:flex;justify-content:center;">
          <img src="static/segmented.png" style="margin-right:10px;width:30%;" />
          <img src="static/masks.png" style="margin-right:10px;width:30%;" />
          <img src="static/diffused.png" style="width:30%;" />
        </div>
        
        ## Installation
        
        ```bash
        pip install samclipdiffusion
        ```
        
        ## Usage
        
        ```bash
        !wget https://dl.fbaipublicfiles.com/segment_anything/sam_vit_h_4b8939.pth
        ```
        
        ```python
        from samclipdiffusion import ImageSegmenter
        segmenter_inp = ImageSegmenter()
        
        image_path = 'image_path'
        search_text = "target object"
        prompt = "how to modify"
        
        inpainted_image = segmenter_inp.inpaint_image(image_path, search_text, prompt)
        ```
        
        ## Examples
        
        [Examples](/examples/) with and w/o installing the package.
        
        ## Citation
        
        This repository is based on the following repos, I just merged them together and made some changes to make it work.
        
        https://github.com/IDEA-Research/Grounded-Segment-Anything/blob/main/grounded_sam.ipynb
        https://github.com/maxi-w/CLIP-SAM/blob/main/main.ipynb
        
        ## TODO
        
        - [ ] Add more examples
        - [ ] Optimize, make it memory efficient, it's awful right now
        - [ ] Add better images to the examples :D
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Description-Content-Type: text/markdown
