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	Requirements updates -testing
Browse files- assets/examples/favicon.ico +0 -0
 - assets/favicon.ico +0 -0
 - requirements.txt +1 -1
 - utils/ai_generator_diffusers_flux.py +2 -2
 - utils/constants.py +1 -1
 - utils/version_info.py +2 -0
 
    	
        assets/examples/favicon.ico
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        assets/favicon.ico
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        requirements.txt
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         @@ -17,7 +17,7 @@ Pillow 
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            numpy
         
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            requests
         
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            # git+https://github.com/huggingface/diffusers
         
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            diffusers
         
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            peft
         
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            opencv-python
         
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            open3d
         
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            numpy
         
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            requests
         
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            # git+https://github.com/huggingface/diffusers
         
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            diffusers[torch]
         
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            peft
         
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            opencv-python
         
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            open3d
         
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        utils/ai_generator_diffusers_flux.py
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         @@ -114,14 +114,14 @@ def generate_image_lowmem( 
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                strength=0.75,
         
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                additional_parameters=None
         
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            ):
         
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                # Retrieve the pipeline class from the mapping
         
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                print(f"device:{device}\nmodel_name:{model_name}\nlora_weights:{lora_weights}\n")
         
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                print(f"\n {get_torch_info()}\n")
         
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                pipeline_class = PIPELINE_CLASSES.get(pipeline_name)
         
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                if not pipeline_class:
         
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                    raise ValueError(f"Unsupported pipeline type '{pipeline_name}'. "
         
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                                    f"Available options: {list(PIPELINE_CLASSES.keys())}")
         
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                device = "cuda" if torch.cuda.is_available() else "cpu"
         
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                # Disable gradient calculations
         
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                with torch.no_grad():
         
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                strength=0.75,
         
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                additional_parameters=None
         
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            ):
         
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                print(f"\n {get_torch_info()}\n")
         
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                # Retrieve the pipeline class from the mapping
         
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                pipeline_class = PIPELINE_CLASSES.get(pipeline_name)
         
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                if not pipeline_class:
         
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                    raise ValueError(f"Unsupported pipeline type '{pipeline_name}'. "
         
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                                    f"Available options: {list(PIPELINE_CLASSES.keys())}")
         
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                device = "cuda" if torch.cuda.is_available() else "cpu"
         
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                print(f"device:{device}\nmodel_name:{model_name}\nlora_weights:{lora_weights}\n")
         
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                # Disable gradient calculations
         
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                with torch.no_grad():
         
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        utils/constants.py
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         @@ -15,7 +15,7 @@ os.environ["PYTORCH_NVML_BASED_CUDA_CHECK"] = "1" 
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            os.environ["CUDA_VISIBLE_DEVICES"] = "0,1,2,3"
         
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            # constants.py contains all the constants used in the project
         
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            -
            os.environ["HF_TOKEN"] = ""
         
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            HF_API_TOKEN = os.getenv("HF_TOKEN")
         
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            default_lut_example_img = "./LUT/daisy.jpg"
         
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            os.environ["CUDA_VISIBLE_DEVICES"] = "0,1,2,3"
         
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            # constants.py contains all the constants used in the project
         
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            #os.environ["HF_TOKEN"] = ""
         
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            HF_API_TOKEN = os.getenv("HF_TOKEN")
         
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            default_lut_example_img = "./LUT/daisy.jpg"
         
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        utils/version_info.py
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         @@ -76,6 +76,8 @@ def versions_html(): 
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                     • 
         
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                    transformers: {get_transformers_version()}
         
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                     • 
         
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                    gradio: {gr.__version__}
         
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                     • 
         
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                    {toggle_dark_link}
         
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                     • 
         
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                    transformers: {get_transformers_version()}
         
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                     • 
         
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                    xformers: {get_xformers_version()}
         
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                     • 
         
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                    gradio: {gr.__version__}
         
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                     • 
         
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                    {toggle_dark_link}
         
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