Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
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@@ -8,6 +8,7 @@ import random
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import numpy as np
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import os
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import subprocess
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# Install flash-attn
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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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@@ -31,6 +32,13 @@ enhancer_long = pipeline("summarization", model="gokaygokay/Lamini-Prompt-Enchan
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MAX_SEED = np.iinfo(np.int32).max
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MAX_IMAGE_SIZE = 1024
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# Florence caption function
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@spaces.GPU
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def florence_caption(image):
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@@ -61,7 +69,7 @@ def enhance_prompt(input_prompt):
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enhanced_text = result[0]['summary_text']
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return enhanced_text
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@spaces.GPU(duration=
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def process_workflow(image, text_prompt, use_enhancer, seed, randomize_seed, width, height, guidance_scale, num_inference_steps, negative_prompt="", progress=gr.Progress(track_tqdm=True)):
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if image is not None:
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# Convert image to PIL if it's not already
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@@ -125,7 +133,7 @@ with gr.Blocks(css=custom_css, theme=gr.themes.Soft(primary_hue="blue", secondar
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with gr.Row():
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with gr.Column(scale=1):
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with gr.Group(elem_classes="input-group"):
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input_image = gr.Image(label="Input Image (Florence-2 Captioner)")
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with gr.Accordion("Advanced Settings", open=False):
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text_prompt = gr.Textbox(label="Text Prompt (optional, used if no image is uploaded)")
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import numpy as np
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import os
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import subprocess
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from huggingface_hub import hf_hub_download
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# Install flash-attn
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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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MAX_SEED = np.iinfo(np.int32).max
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MAX_IMAGE_SIZE = 1024
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hf_hub_download(
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repo_id="stabilityai/stable-diffusion-3.5-large-turbo",
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filename="LICENSE.md",
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local_dir = "./models",
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token = huggingface_token
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)
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# Florence caption function
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@spaces.GPU
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def florence_caption(image):
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enhanced_text = result[0]['summary_text']
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return enhanced_text
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@spaces.GPU(duration=60)
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def process_workflow(image, text_prompt, use_enhancer, seed, randomize_seed, width, height, guidance_scale, num_inference_steps, negative_prompt="", progress=gr.Progress(track_tqdm=True)):
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if image is not None:
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# Convert image to PIL if it's not already
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with gr.Row():
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with gr.Column(scale=1):
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with gr.Group(elem_classes="input-group"):
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input_image = gr.Image(label="Input Image (Florence-2 Captioner)", height=512)
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with gr.Accordion("Advanced Settings", open=False):
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text_prompt = gr.Textbox(label="Text Prompt (optional, used if no image is uploaded)")
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