Update app.py
Browse files
app.py
CHANGED
@@ -41,6 +41,7 @@ batch_size = -1
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width = int(os.getenv("IMAGE_WIDTH", "512"))
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height = int(os.getenv("IMAGE_HEIGHT", "512"))
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num_images = int(os.getenv("NUM_IMAGES", "1"))
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class CustomOVModelVaeDecoder(OVModelVaeDecoder):
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def __init__(
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@@ -78,7 +79,6 @@ def save_images(image_array, profile: gr.OAuthProfile | None, metadata: dict):
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def generate(
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prompt: str,
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seed: int = 0,
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-
guidance_scale: float = 1.0,
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num_inference_steps: int = 4,
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randomize_seed: bool = False,
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progress = gr.Progress(track_tqdm=True),
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@@ -88,6 +88,7 @@ def generate(
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global width
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global height
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global num_images
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seed = randomize_seed_fn(seed, randomize_seed)
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np.random.seed(seed)
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@@ -172,7 +173,6 @@ with gr.Blocks(css="style.css") as demo:
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inputs=[
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prompt,
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seed,
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1.0,
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num_inference_steps,
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randomize_seed
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],
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width = int(os.getenv("IMAGE_WIDTH", "512"))
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height = int(os.getenv("IMAGE_HEIGHT", "512"))
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num_images = int(os.getenv("NUM_IMAGES", "1"))
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guidance_scale = float(os.getenv("GUIDANCE_SCALE", "1.0"))
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class CustomOVModelVaeDecoder(OVModelVaeDecoder):
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def __init__(
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def generate(
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prompt: str,
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seed: int = 0,
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num_inference_steps: int = 4,
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randomize_seed: bool = False,
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progress = gr.Progress(track_tqdm=True),
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global width
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global height
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global num_images
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global guidance_scale
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seed = randomize_seed_fn(seed, randomize_seed)
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np.random.seed(seed)
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inputs=[
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prompt,
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seed,
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num_inference_steps,
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randomize_seed
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],
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