├── requirements.txt ├── README.md ├── .gitignore ├── app.py └── LICENSE /requirements.txt: -------------------------------------------------------------------------------- 1 | gradio 2 | git+https://github.com/huggingface/transformers 3 | safetensors 4 | accelerate 5 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Image Captioning with Gradio 2 | 3 | This repo provides a simple GUI application for using the [Qwen2-VL-7B-Captioner-Relaxed](https://huggingface.co/Ertugrul/Qwen2-VL-7B-Captioner-Relaxed) model for image captioning. It is 4 | ## Features 5 | 6 | - Upload an image and generate a caption. 7 | - Select from predefined system prompts or enter a custom prompt. 8 | - Automatically load and initialize the model on the first caption generation. 9 | 10 | ## Setup 11 | 12 | ### Prerequisites 13 | 14 | - Python 3.9 or higher 15 | - pip (Python package installer) 16 | - GPU with CUDA support with at least of 16GB VRAM 17 | - 16 GB of storage for the model weights 18 | 19 | ### Installation 20 | 21 | 1. Clone the repository: 22 | 23 | ```bash 24 | git clone https://github.com/ertugrul-dmr/qwen2vl-captioner-gui.git 25 | ``` 26 | ```bash 27 | cd qwen2vl-captioner-gui 28 | ``` 29 | 30 | 2. Install the required packages: 31 | 32 | ### For Linux: 33 | ```bash 34 | python3 -m venv venv 35 | source venv/bin/activate 36 | pip3 install torch 37 | pip3 install -r requirements.txt 38 | ``` 39 | 40 | ### For Windows: 41 | ```bash 42 | python -m venv venv 43 | .\venv\Scripts\activate 44 | pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121 45 | pip install -r requirements.txt 46 | ``` 47 | 48 | ### Running the Application 49 | 50 | 1. Run the `app.py` script: 51 | 52 | ```bash 53 | python app.py 54 | ``` 55 | 56 | 2. Open your web browser and go to `http://localhost:7860` to access the Gradio interface. 57 | 58 | ## Usage 59 | 60 | 1. Upload an image by clicking on the image input box. 61 | 2. Select a system prompt from the dropdown menu or enter a custom prompt or leave as default. 62 | 3. Click the "Generate Caption" button to generate a caption for the image. 63 | 4. The generated caption will be displayed in the "Generated Caption" textbox. 64 | 65 | ## License 66 | 67 | This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details. 68 | 69 | ## Acknowledgements 70 | 71 | - [Gradio](https://gradio.app/) 72 | - [Hugging Face Transformers](https://huggingface.co/transformers/) 73 | - [Qwen2-VL](https://huggingface.co/Qwen/Qwen2-VL-7B-Instruct) 74 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | share/python-wheels/ 24 | *.egg-info/ 25 | .installed.cfg 26 | *.egg 27 | MANIFEST 28 | 29 | # PyInstaller 30 | # Usually these files are written by a python script from a template 31 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 32 | *.manifest 33 | *.spec 34 | 35 | # Installer logs 36 | pip-log.txt 37 | pip-delete-this-directory.txt 38 | 39 | # Unit test / coverage reports 40 | htmlcov/ 41 | .tox/ 42 | .nox/ 43 | .coverage 44 | .coverage.* 45 | .cache 46 | nosetests.xml 47 | coverage.xml 48 | *.cover 49 | *.py,cover 50 | .hypothesis/ 51 | .pytest_cache/ 52 | cover/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | db.sqlite3-journal 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | .pybuilder/ 76 | target/ 77 | 78 | # Jupyter Notebook 79 | .ipynb_checkpoints 80 | 81 | # IPython 82 | profile_default/ 83 | ipython_config.py 84 | 85 | # pyenv 86 | # For a library or package, you might want to ignore these files since the code is 87 | # intended to run in multiple environments; otherwise, check them in: 88 | # .python-version 89 | 90 | # pipenv 91 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 92 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 93 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 94 | # install all needed dependencies. 95 | #Pipfile.lock 96 | 97 | # poetry 98 | # Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. 99 | # This is especially recommended for binary packages to ensure reproducibility, and is more 100 | # commonly ignored for libraries. 101 | # https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control 102 | #poetry.lock 103 | 104 | # pdm 105 | # Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. 106 | #pdm.lock 107 | # pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it 108 | # in version control. 109 | # https://pdm.fming.dev/latest/usage/project/#working-with-version-control 110 | .pdm.toml 111 | .pdm-python 112 | .pdm-build/ 113 | 114 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm 115 | __pypackages__/ 116 | 117 | # Celery stuff 118 | celerybeat-schedule 119 | celerybeat.pid 120 | 121 | # SageMath parsed files 122 | *.sage.py 123 | 124 | # Environments 125 | .env 126 | .venv 127 | env/ 128 | venv/ 129 | ENV/ 130 | env.bak/ 131 | venv.bak/ 132 | 133 | # Spyder project settings 134 | .spyderproject 135 | .spyproject 136 | 137 | # Rope project settings 138 | .ropeproject 139 | 140 | # mkdocs documentation 141 | /site 142 | 143 | # mypy 144 | .mypy_cache/ 145 | .dmypy.json 146 | dmypy.json 147 | 148 | # Pyre type checker 149 | .pyre/ 150 | 151 | # pytype static type analyzer 152 | .pytype/ 153 | 154 | # Cython debug symbols 155 | cython_debug/ 156 | 157 | # PyCharm 158 | # JetBrains specific template is maintained in a separate JetBrains.gitignore that can 159 | # be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore 160 | # and can be added to the global gitignore or merged into this file. For a more nuclear 161 | # option (not recommended) you can uncomment the following to ignore the entire idea folder. 162 | #.idea/ 163 | -------------------------------------------------------------------------------- /app.py: -------------------------------------------------------------------------------- 1 | import gradio as gr 2 | from PIL import Image 3 | from transformers import Qwen2VLForConditionalGeneration, AutoProcessor 4 | import torch 5 | import warnings 6 | import sys 7 | from io import StringIO 8 | import gc 9 | 10 | # Suppress warnings 11 | warnings.filterwarnings("ignore") 12 | 13 | # Initialize model and processor variables 14 | model = None 15 | processor = None 16 | 17 | # Create a custom StringIO object to capture print statements 18 | class CustomStringIO(StringIO): 19 | def __init__(self, callback): 20 | super().__init__() 21 | self.callback = callback 22 | 23 | def write(self, string): 24 | super().write(string) 25 | self.callback(self.getvalue()) 26 | 27 | def load_model(status_box): 28 | global model, processor 29 | model_id = "Ertugrul/Qwen2-VL-7B-Captioner-Relaxed" 30 | 31 | print("Loading model...") 32 | if isinstance(status_box, gr.components.Textbox): 33 | status_box.update(value="Loading model...") 34 | 35 | model = Qwen2VLForConditionalGeneration.from_pretrained( 36 | model_id, 37 | torch_dtype=torch.bfloat16, 38 | device_map="auto" 39 | ) 40 | 41 | processor = AutoProcessor.from_pretrained(model_id, min_pixels=512*512, max_pixels=1280*1280) 42 | 43 | print("Model loaded successfully!") 44 | if isinstance(status_box, gr.components.Textbox): 45 | status_box.update(value="Model loaded successfully!") 46 | return "Model loaded successfully!" 47 | 48 | def resize_image(image, longest_size): 49 | width, height = image.size 50 | if width > height: 51 | new_width = longest_size 52 | new_height = int(height * (longest_size / width)) 53 | else: 54 | new_height = longest_size 55 | new_width = int(width * (longest_size / height)) 56 | return image.resize((new_width, new_height), Image.LANCZOS) 57 | 58 | def clean_memory(): 59 | gc.collect() 60 | torch.cuda.empty_cache() 61 | 62 | def generate_caption(image, longest_size, system_prompt, status_box): 63 | global model, processor 64 | if model is None or processor is None: 65 | load_model(status_box) 66 | 67 | try: 68 | # Convert image to PIL Image and resize 69 | image = Image.fromarray(image).convert('RGB') 70 | image = resize_image(image, longest_size) 71 | 72 | print("Processing image...") 73 | if isinstance(status_box, gr.components.Textbox): 74 | status_box.update(value="Processing image...") 75 | 76 | # Prepare conversation 77 | conversation = [] 78 | # Add system prompt if not None 79 | if system_prompt: 80 | conversation.append({ 81 | "role": "system", 82 | "content": system_prompt 83 | }) 84 | conversation.append({ 85 | "role": "user", 86 | "content": [ 87 | {"type": "image"}, 88 | {"type": "text", "text": "Describe this image."}, 89 | ], 90 | }) 91 | 92 | # Process input 93 | text_prompt = processor.apply_chat_template(conversation, add_generation_prompt=True) 94 | inputs = processor(text=[text_prompt], images=[image], padding=True, return_tensors="pt") 95 | inputs = inputs.to("cuda" if torch.cuda.is_available() else "cpu") 96 | 97 | print("Generating caption...") 98 | if isinstance(status_box, gr.components.Textbox): 99 | status_box.update(value="Generating caption...") 100 | 101 | # Generate caption 102 | with torch.no_grad(): 103 | with torch.autocast(device_type="cuda" if torch.cuda.is_available() else "cpu", dtype=torch.bfloat16): 104 | output_ids = model.generate(**inputs, max_new_tokens=384, do_sample=True, temperature=0.7, use_cache=True, top_k=50) 105 | 106 | # Decode output 107 | generated_ids = output_ids[0][len(inputs.input_ids[0]):] 108 | output_text = processor.decode(generated_ids, skip_special_tokens=True, clean_up_tokenization_spaces=True) 109 | 110 | print("Caption generated successfully") 111 | if isinstance(status_box, gr.components.Textbox): 112 | status_box.update(value="Caption generated successfully") 113 | 114 | # Delete variables that will be recreated for next generation 115 | del image, conversation, text_prompt, inputs, output_ids, generated_ids 116 | 117 | # Clean memory after generation 118 | clean_memory() 119 | 120 | return output_text, "Caption generated successfully" 121 | except Exception as e: 122 | error_message = f"An error occurred: {str(e)}" 123 | print(error_message) 124 | if isinstance(status_box, gr.components.Textbox): 125 | status_box.update(value=error_message) 126 | return error_message, "Error during caption generation" 127 | 128 | # Create Gradio interface 129 | with gr.Blocks() as iface: 130 | gr.Markdown("# Image Captioning") 131 | gr.Markdown("Upload an image and click 'Generate Caption' to get a description. The model will be loaded(downloaded first time) automatically when you generate the first caption.") 132 | 133 | with gr.Row(): 134 | image_input = gr.Image(type="numpy") 135 | with gr.Column(): 136 | longest_size = gr.Slider(minimum=512, maximum=2048, value=768, step=64, label="Longest Size (pixels)") 137 | 138 | # Add predefined system prompts 139 | system_prompt_choices = [ 140 | "Use full description", 141 | "Use short description", 142 | "Use brief description", 143 | "Use detailed description", 144 | "Describe the image in a poetic way (Experimental)", 145 | "Single word description", 146 | "Custom" 147 | ] 148 | 149 | system_prompt_mapping = { 150 | "Use full description": None, 151 | "Use short description": "Use maximum of 10 words.", 152 | "Use brief description": "Use maximum of 50 words.", 153 | "Use detailed description": "Use maximum of 100 words.", 154 | "Describe the image in a poetic way (Experimental)": "Describe the image in a poetic way.", 155 | "Single word description": "Describe the image in a word only. Nothing more. Strict rule. Only 1 word!!!", 156 | "Custom": "Custom" 157 | } 158 | 159 | system_prompt_dropdown = gr.Dropdown( 160 | choices=system_prompt_choices, 161 | label="System Prompt", 162 | value="Use full description" 163 | ) 164 | system_prompt_input = gr.Textbox( 165 | label="Custom System Prompt", 166 | placeholder="Enter a custom system prompt", 167 | visible=False 168 | ) 169 | 170 | generate_button = gr.Button("Generate Caption", variant="primary") 171 | 172 | with gr.Row(): 173 | caption_output = gr.Textbox(label="Generated Caption") 174 | model_status = gr.Textbox(label="Model Status", interactive=False) 175 | 176 | def update_system_prompt_visibility(choice): 177 | return gr.update(visible=choice == "Custom") 178 | 179 | system_prompt_dropdown.change( 180 | fn=update_system_prompt_visibility, 181 | inputs=system_prompt_dropdown, 182 | outputs=system_prompt_input 183 | ) 184 | 185 | def get_system_prompt(dropdown_choice, custom_prompt): 186 | if dropdown_choice == "Custom": 187 | return custom_prompt 188 | else: 189 | return system_prompt_mapping[dropdown_choice] 190 | 191 | generate_button.click( 192 | fn=generate_caption, 193 | inputs=[ 194 | image_input, 195 | longest_size, 196 | gr.Textbox(value=get_system_prompt, inputs=[system_prompt_dropdown, system_prompt_input], visible=False), 197 | model_status 198 | ], 199 | outputs=[caption_output, model_status] 200 | ) 201 | 202 | # Launch the interface 203 | iface.launch() 204 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | Apache License 2 | Version 2.0, January 2004 3 | http://www.apache.org/licenses/ 4 | 5 | TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 6 | 7 | 1. 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