blip-base activated
Browse files
app.py
CHANGED
@@ -11,8 +11,8 @@ torch.hub.download_url_to_file('http://images.cocodataset.org/val2017/0000000397
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torch.hub.download_url_to_file('https://huggingface.co/datasets/nielsr/textcaps-sample/resolve/main/stop_sign.png', 'stop_sign.png')
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torch.hub.download_url_to_file('https://cdn.openai.com/dall-e-2/demos/text2im/astronaut/horse/photo/0.jpg', 'astronaut.jpg')
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git_processor_base = AutoProcessor.from_pretrained("microsoft/git-base-coco")
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git_model_base = AutoModelForCausalLM.from_pretrained("microsoft/git-base-coco")
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# git_processor_large_coco = AutoProcessor.from_pretrained("microsoft/git-large-coco")
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# git_model_large_coco = AutoModelForCausalLM.from_pretrained("microsoft/git-large-coco")
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@@ -43,7 +43,7 @@ blip_model_base = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-
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device = "cuda" if torch.cuda.is_available() else "cpu"
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git_model_base.to(device)
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blip_model_base.to(device)
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# git_model_large_coco.to(device)
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# git_model_large_textcaps.to(device)
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@@ -76,7 +76,7 @@ def generate_caption_coca(model, transform, image):
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def generate_captions(image):
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caption_git_base = generate_caption(git_processor_base, git_model_base, image)
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# caption_git_large_coco = generate_caption(git_processor_large_coco, git_model_large_coco, image)
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@@ -95,14 +95,14 @@ def generate_captions(image):
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# caption_blip2_8_bit = generate_caption(blip2_processor_8_bit, blip2_model_8_bit, image, use_float_16=True).strip()
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# return caption_git_large_coco, caption_git_large_textcaps, caption_blip_large, caption_coca, caption_blip2_8_bit
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return
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examples = [["cats.jpg"], ["stop_sign.png"], ["astronaut.jpg"]]
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# outputs = [gr.outputs.Textbox(label="Caption generated by GIT-large fine-tuned on COCO"), gr.outputs.Textbox(label="Caption generated by GIT-large fine-tuned on TextCaps"), gr.outputs.Textbox(label="Caption generated by BLIP-large"), gr.outputs.Textbox(label="Caption generated by CoCa"), gr.outputs.Textbox(label="Caption generated by BLIP-2 OPT 6.7b")]
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outputs = [
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gr.outputs.Textbox(label="Caption generated by GIT-base fine-tuned on COCO"),
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# gr.outputs.Textbox(label="Caption generated by GIT-large fine-tuned on COCO"),
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# gr.outputs.Textbox(label="Caption generated by GIT-large fine-tuned on TextCaps"),
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gr.outputs.Textbox(label="Caption generated by BLIP-base"),
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@@ -110,7 +110,7 @@ outputs = [
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# gr.outputs.Textbox(label="Caption generated by vitgpt")
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]
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title = "Interactive demo:
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description = "Gradio Demo to compare GIT, BLIP, CoCa, and BLIP-2, 4 state-of-the-art vision+language models. To use it, simply upload your image and click 'submit', or click one of the examples to load them. Read more at the links below."
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article = "<p style='text-align: center'><a href='https://huggingface.co/docs/transformers/main/model_doc/blip' target='_blank'>BLIP docs</a> | <a href='https://huggingface.co/docs/transformers/main/model_doc/git' target='_blank'>GIT docs</a></p>"
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torch.hub.download_url_to_file('https://huggingface.co/datasets/nielsr/textcaps-sample/resolve/main/stop_sign.png', 'stop_sign.png')
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torch.hub.download_url_to_file('https://cdn.openai.com/dall-e-2/demos/text2im/astronaut/horse/photo/0.jpg', 'astronaut.jpg')
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# git_processor_base = AutoProcessor.from_pretrained("microsoft/git-base-coco")
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# git_model_base = AutoModelForCausalLM.from_pretrained("microsoft/git-base-coco")
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# git_processor_large_coco = AutoProcessor.from_pretrained("microsoft/git-large-coco")
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# git_model_large_coco = AutoModelForCausalLM.from_pretrained("microsoft/git-large-coco")
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device = "cuda" if torch.cuda.is_available() else "cpu"
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# git_model_base.to(device)
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blip_model_base.to(device)
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# git_model_large_coco.to(device)
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# git_model_large_textcaps.to(device)
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def generate_captions(image):
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# caption_git_base = generate_caption(git_processor_base, git_model_base, image)
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# caption_git_large_coco = generate_caption(git_processor_large_coco, git_model_large_coco, image)
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# caption_blip2_8_bit = generate_caption(blip2_processor_8_bit, blip2_model_8_bit, image, use_float_16=True).strip()
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# return caption_git_large_coco, caption_git_large_textcaps, caption_blip_large, caption_coca, caption_blip2_8_bit
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return caption_blip_base
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examples = [["cats.jpg"], ["stop_sign.png"], ["astronaut.jpg"]]
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# outputs = [gr.outputs.Textbox(label="Caption generated by GIT-large fine-tuned on COCO"), gr.outputs.Textbox(label="Caption generated by GIT-large fine-tuned on TextCaps"), gr.outputs.Textbox(label="Caption generated by BLIP-large"), gr.outputs.Textbox(label="Caption generated by CoCa"), gr.outputs.Textbox(label="Caption generated by BLIP-2 OPT 6.7b")]
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outputs = [
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# gr.outputs.Textbox(label="Caption generated by GIT-base fine-tuned on COCO"),
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# gr.outputs.Textbox(label="Caption generated by GIT-large fine-tuned on COCO"),
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# gr.outputs.Textbox(label="Caption generated by GIT-large fine-tuned on TextCaps"),
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gr.outputs.Textbox(label="Caption generated by BLIP-base"),
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# gr.outputs.Textbox(label="Caption generated by vitgpt")
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]
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title = "Interactive demo: blip-base"
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description = "Gradio Demo to compare GIT, BLIP, CoCa, and BLIP-2, 4 state-of-the-art vision+language models. To use it, simply upload your image and click 'submit', or click one of the examples to load them. Read more at the links below."
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article = "<p style='text-align: center'><a href='https://huggingface.co/docs/transformers/main/model_doc/blip' target='_blank'>BLIP docs</a> | <a href='https://huggingface.co/docs/transformers/main/model_doc/git' target='_blank'>GIT docs</a></p>"
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