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Yaron Koresh
commited on
Update app.py
Browse files
app.py
CHANGED
@@ -429,13 +429,12 @@ root.addHandler(handler)
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# constant data
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base = "black-forest-labs/FLUX.1-schnell"
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pegasus_name = "google/pegasus-xsum"
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# precision data
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seq=256
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width=
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height=
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image_steps=8
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img_accu=0
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@@ -509,7 +508,7 @@ def upscaler(
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prompt: str = "Photorealistic, Hyperrealistic, Realistic Photography, High-Quality Photography, Natural.",
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negative_prompt: str = "Distorted, Discontinuous, Blurry, Doll-Like, Overly-Plastic, Low-Quality, Painted, Smoothed, Artificial, Phony, Gaudy, Digital Effects.",
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seed: int = int(str(random.random()).split(".")[1]),
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upscale_factor: int =
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controlnet_scale: float = 0.6,
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controlnet_decay: float = 1.0,
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condition_scale: int = 6,
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@@ -539,7 +538,7 @@ def upscaler(
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tile_size=(tile_height, tile_width),
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denoise_strength=denoise_strength,
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num_inference_steps=num_inference_steps,
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loras_scale={"more_details":
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solver_type=solver_type,
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)
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@@ -548,11 +547,11 @@ def upscaler(
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return enhanced_image
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def summarize_text(
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text, max_length=
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):
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log(f'CALL summarize_text')
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summ = pipeline("summarization", model="
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summary = summ("summarize: " + text)[0]["summary_text"]
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log(f'RET summarize_text with summary as {summary}')
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return summary
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# constant data
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base = "black-forest-labs/FLUX.1-schnell"
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# precision data
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seq=256
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width=1536
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height=1536
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image_steps=8
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img_accu=0
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prompt: str = "Photorealistic, Hyperrealistic, Realistic Photography, High-Quality Photography, Natural.",
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negative_prompt: str = "Distorted, Discontinuous, Blurry, Doll-Like, Overly-Plastic, Low-Quality, Painted, Smoothed, Artificial, Phony, Gaudy, Digital Effects.",
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seed: int = int(str(random.random()).split(".")[1]),
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upscale_factor: int = 4,
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controlnet_scale: float = 0.6,
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controlnet_decay: float = 1.0,
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condition_scale: int = 6,
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tile_size=(tile_height, tile_width),
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denoise_strength=denoise_strength,
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num_inference_steps=num_inference_steps,
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loras_scale={"more_details": 0.5, "sdxl_render": 1.0},
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solver_type=solver_type,
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)
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return enhanced_image
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def summarize_text(
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text, min_length=4, max_length=12
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):
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log(f'CALL summarize_text')
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summ = pipeline("summarization", model="facebook/bart-large-cnn")
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summary = summ("summarize: " + text, max_length=max_length, min_length=min_length, do_sample=False)[0]["summary_text"]
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log(f'RET summarize_text with summary as {summary}')
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return summary
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