Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
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@@ -56,26 +56,32 @@ def process_input(input_image, upscale_factor, **kwargs):
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w_original, h_original = w, h
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aspect_ratio = w / h
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if w * h * upscale_factor**2 > MAX_PIXEL_BUDGET:
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warnings.warn(
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f"Requested output image is too large ({w * upscale_factor}x{h * upscale_factor}). Resizing to ({int(aspect_ratio * MAX_PIXEL_BUDGET ** 0.5 // upscale_factor), int(MAX_PIXEL_BUDGET ** 0.5 // aspect_ratio // upscale_factor)}) pixels."
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)
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input_image = input_image.resize(
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(
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int(aspect_ratio * MAX_PIXEL_BUDGET**0.5 // upscale_factor),
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int(MAX_PIXEL_BUDGET**0.5 // aspect_ratio // upscale_factor),
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)
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)
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# resize to multiple of 8
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w, h = input_image.size
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w = w - w % 8
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h = h - h % 8
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return input_image.resize((w, h)), w_original, h_original
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@spaces.GPU
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def infer(
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seed,
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randomize_seed,
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@@ -88,7 +94,9 @@ def infer(
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if randomize_seed:
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seed = random.randint(0, MAX_SEED)
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true_input_image = input_image
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input_image, w_original, h_original = process_input(
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# rescale with upscale factor
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w, h = input_image.size
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@@ -107,6 +115,11 @@ def infer(
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generator=generator,
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).images[0]
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# resize to target desired size
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image = image.resize((w_original * upscale_factor, h_original * upscale_factor))
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image.save("output.jpg")
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w_original, h_original = w, h
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aspect_ratio = w / h
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was_resized = False
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if w * h * upscale_factor**2 > MAX_PIXEL_BUDGET:
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warnings.warn(
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f"Requested output image is too large ({w * upscale_factor}x{h * upscale_factor}). Resizing to ({int(aspect_ratio * MAX_PIXEL_BUDGET ** 0.5 // upscale_factor), int(MAX_PIXEL_BUDGET ** 0.5 // aspect_ratio // upscale_factor)}) pixels."
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)
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gr.Info(
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f"Requested output image is too large ({w * upscale_factor}x{h * upscale_factor}). Resizing to ({int(aspect_ratio * MAX_PIXEL_BUDGET ** 0.5 // upscale_factor), int(MAX_PIXEL_BUDGET ** 0.5 // aspect_ratio // upscale_factor)}) input pixels budget."
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)
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input_image = input_image.resize(
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(
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int(aspect_ratio * MAX_PIXEL_BUDGET**0.5 // upscale_factor),
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int(MAX_PIXEL_BUDGET**0.5 // aspect_ratio // upscale_factor),
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)
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)
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was_resized = True
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# resize to multiple of 8
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w, h = input_image.size
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w = w - w % 8
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h = h - h % 8
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return input_image.resize((w, h)), w_original, h_original, was_resized
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@spaces.GPU(duration=75)
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def infer(
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seed,
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randomize_seed,
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if randomize_seed:
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seed = random.randint(0, MAX_SEED)
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true_input_image = input_image
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input_image, w_original, h_original, was_resized = process_input(
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input_image, upscale_factor
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)
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# rescale with upscale factor
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w, h = input_image.size
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generator=generator,
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).images[0]
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if was_resized:
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gr.Info(
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f"Resized output image to targeted {w_original * upscale_factor}x{h_original * upscale_factor} size."
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)
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# resize to target desired size
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image = image.resize((w_original * upscale_factor, h_original * upscale_factor))
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image.save("output.jpg")
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