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import gradio as gr |
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from transformers import AutoProcessor, AutoModelForCausalLM |
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import spaces |
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import re |
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from PIL import Image |
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import subprocess |
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subprocess.run('pip install flash-attn --no-build-isolation', env={'FLASH_ATTENTION_SKIP_CUDA_BUILD': "TRUE"}, shell=True) |
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model = AutoModelForCausalLM.from_pretrained('gokaygokay/Florence-2-SD3-Captioner', trust_remote_code=True).to("cuda").eval() |
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processor = AutoProcessor.from_pretrained('gokaygokay/Florence-2-SD3-Captioner', trust_remote_code=True) |
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TITLE = "# [Florence-2 SD3 Long Captioner](https://huggingface.co/gokaygokay/Florence-2-SD3-Captioner/)" |
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def modify_caption(caption: str) -> str: |
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""" |
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Removes specific prefixes from captions if present, otherwise returns the original caption. |
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Args: |
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caption (str): A string containing a caption. |
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Returns: |
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str: The caption with the prefix removed if it was present, or the original caption. |
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""" |
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prefix_substrings = [ |
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('captured from ', ''), |
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('captured at ', '') |
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] |
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pattern = '|'.join([re.escape(opening) for opening, _ in prefix_substrings]) |
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replacers = {opening.lower(): replacer for opening, replacer in prefix_substrings} |
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def replace_fn(match): |
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return replacers[match.group(0).lower()] |
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modified_caption = re.sub(pattern, replace_fn, caption, count=1, flags=re.IGNORECASE) |
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return modified_caption if modified_caption != caption else caption |
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@spaces.GPU |
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def run_example(image): |
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image = Image.fromarray(image) |
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task_prompt = "<DESCRIPTION>" |
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prompt = task_prompt + "Describe this image in great detail." |
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if image.mode != "RGB": |
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image = image.convert("RGB") |
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inputs = processor(text=prompt, images=image, return_tensors="pt").to("cuda") |
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generated_ids = model.generate( |
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input_ids=inputs["input_ids"], |
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pixel_values=inputs["pixel_values"], |
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max_new_tokens=1024, |
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num_beams=3 |
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) |
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generated_text = processor.batch_decode(generated_ids, skip_special_tokens=False)[0] |
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parsed_answer = processor.post_process_generation(generated_text, task=task_prompt, image_size=(image.width, image.height)) |
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return modify_caption(parsed_answer["<DESCRIPTION>"]) |
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css = """ |
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#output { |
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height: 500px; |
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overflow: auto; |
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border: 1px solid #ccc; |
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} |
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""" |
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with gr.Blocks(css=css) as demo: |
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gr.Markdown(TITLE) |
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with gr.Tab(label="Florence-2 SD3 Prompts"): |
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with gr.Row(): |
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with gr.Column(): |
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input_img = gr.Image(label="Input Picture") |
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submit_btn = gr.Button(value="Submit") |
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with gr.Column(): |
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output_text = gr.Textbox(label="Output Text") |
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gr.Examples( |
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[["image1.jpg"], ["image2.jpg"], ["image3.png"], ["image4.jpg"], ["image5.jpg"], ["image6.PNG"]], |
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inputs = [input_img], |
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outputs = [output_text], |
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fn=run_example, |
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label='Try captioning on below examples' |
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) |
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submit_btn.click(run_example, [input_img], [output_text]) |
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demo.launch(debug=True) |