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from __future__ import annotations |
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import gradio as gr |
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import torch |
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from gradio_client import Client, file |
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DESCRIPTION = "# Comparing image captioning models" |
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ORIGINAL_SPACE_INFO = """\ |
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- [GIT-large fine-tuned on COCO](https://huggingface.co/spaces/hysts/image-captioning-with-git) |
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- [BLIP-large](https://huggingface.co/spaces/hysts/image-captioning-with-blip) |
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- [BLIP-2 OPT 6.7B](https://huggingface.co/spaces/merve/BLIP2-with-transformers) |
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- [BLIP-2 T5-XXL](https://huggingface.co/spaces/hysts/BLIP2) |
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- [InstructBLIP](https://huggingface.co/spaces/hysts/InstructBLIP) |
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- [Fuyu-8B](https://huggingface.co/spaces/adept/fuyu-8b-demo) |
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""" |
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torch.hub.download_url_to_file("http://images.cocodataset.org/val2017/000000039769.jpg", "cats.jpg") |
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torch.hub.download_url_to_file( |
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"https://huggingface.co/datasets/nielsr/textcaps-sample/resolve/main/stop_sign.png", "stop_sign.png" |
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) |
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torch.hub.download_url_to_file( |
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"https://cdn.openai.com/dall-e-2/demos/text2im/astronaut/horse/photo/0.jpg", "astronaut.jpg" |
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) |
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def generate_caption_git(image_path: str) -> str: |
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try: |
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client = Client("hysts/image-captioning-with-git") |
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return client.predict(file(image_path), api_name="/caption") |
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except Exception: |
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gr.Warning("The GIT-large Space is currently unavailable. Please try again later.") |
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return "" |
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def generate_caption_blip(image_path: str) -> str: |
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try: |
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client = Client("hysts/image-captioning-with-blip") |
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return client.predict(file(image_path), "A picture of", api_name="/caption") |
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except Exception: |
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gr.Warning("The BLIP-large Space is currently unavailable. Please try again later.") |
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return "" |
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def generate_caption_blip2_opt(image_path: str) -> str: |
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try: |
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client = Client("merve/BLIP2-with-transformers") |
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return client.predict( |
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file(image_path), |
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"Beam search", |
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1, |
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1, |
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1.5, |
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api_name="/caption", |
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) |
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except Exception: |
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gr.Warning("The BLIP2 OPT6.7B Space is currently unavailable. Please try again later.") |
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return "" |
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def generate_caption_blip2_t5xxl(image_path: str) -> str: |
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try: |
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client = Client("hysts/BLIP2") |
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return client.predict( |
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file(image_path), |
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"Beam search", |
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1, |
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1, |
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1.5, |
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50, |
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1, |
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5, |
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0.9, |
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api_name="/caption", |
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) |
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except Exception: |
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gr.Warning("The BLIP2 T5-XXL Space is currently unavailable. Please try again later.") |
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return "" |
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def generate_caption_instructblip(image_path: str) -> str: |
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try: |
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client = Client("hysts/InstructBLIP") |
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return client.predict( |
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file(image_path), |
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"Describe the image.", |
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"Beam search", |
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5, |
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256, |
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1, |
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0.9, |
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1.5, |
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1.0, |
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1.0, |
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api_name="/run", |
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) |
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except Exception: |
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gr.Warning("The InstructBLIP Space is currently unavailable. Please try again later.") |
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return "" |
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def generate_caption_fuyu(image_path: str) -> str: |
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try: |
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client = Client("adept/fuyu-8b-demo") |
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return client.predict( |
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image_path, |
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"Generate a coco style caption.\n", |
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fn_index=3, |
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) |
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except Exception: |
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gr.Warning("The Fuyu-8B Space is currently unavailable. Please try again later.") |
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return "" |
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with gr.Blocks(css="style.css") as demo: |
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gr.Markdown(DESCRIPTION) |
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with gr.Row(): |
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with gr.Column(): |
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input_image = gr.Image(type="filepath") |
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run_button = gr.Button("Caption") |
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with gr.Column(): |
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out_git = gr.Textbox(label="GIT-large fine-tuned on COCO") |
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out_blip = gr.Textbox(label="BLIP-large") |
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out_blip2_opt = gr.Textbox(label="BLIP-2 OPT 6.7B") |
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out_blip2_t5xxl = gr.Textbox(label="BLIP-2 T5-XXL") |
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out_instructblip = gr.Textbox(label="InstructBLIP") |
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out_fuyu = gr.Textbox(label="Fuyu-8B") |
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gr.Examples( |
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examples=[ |
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"cats.jpg", |
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"stop_sign.png", |
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"astronaut.jpg", |
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], |
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inputs=input_image, |
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) |
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with gr.Accordion(label="The original Spaces can be found here:", open=False): |
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gr.Markdown(ORIGINAL_SPACE_INFO) |
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fn_out_pairs = [ |
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(generate_caption_git, out_git), |
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(generate_caption_blip, out_blip), |
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(generate_caption_blip2_opt, out_blip2_opt), |
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(generate_caption_blip2_t5xxl, out_blip2_t5xxl), |
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(generate_caption_instructblip, out_instructblip), |
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(generate_caption_fuyu, out_fuyu), |
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] |
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for fn, out in fn_out_pairs: |
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run_button.click( |
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fn=fn, |
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inputs=input_image, |
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outputs=out, |
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api_name=False, |
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) |
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if __name__ == "__main__": |
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demo.queue(max_size=20, api_open=False).launch(show_api=False) |
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