Spaces:
Running
Running
Commit
·
66303da
1
Parent(s):
4fe873f
remove unused functions
Browse files
app.py
CHANGED
@@ -35,27 +35,6 @@ def encode_image(image_path):
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return base64.b64encode(image_file.read()).decode('utf-8')
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@spaces.GPU #[uncomment to use ZeroGPU]
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def infer(
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prompt,
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progress=gr.Progress(track_tqdm=True),
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):
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# seed = random.randint(0, MAX_SEED)
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# generator = torch.Generator().manual_seed(seed)
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image = pipe(
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prompt=prompt,
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guidance_scale=0.,
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num_inference_steps=4,
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width=1420,
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height=1080,
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max_sequence_length=256,
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).images[0]
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return image
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@spaces.GPU #[uncomment to use ZeroGPU]
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def generate_description_fn(
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image,
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@@ -128,8 +107,59 @@ with gr.Blocks(css=css) as demo:
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result = gr.Image(label="Result", show_label=False)
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gr.
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gr.on(
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triggers=[generate_button.click],
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return base64.b64encode(image_file.read()).decode('utf-8')
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@spaces.GPU #[uncomment to use ZeroGPU]
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def generate_description_fn(
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image,
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result = gr.Image(label="Result", show_label=False)
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with gr.Accordion("Advanced Settings", open=False):
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negative_prompt = gr.Text(
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label="Negative prompt",
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max_lines=1,
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placeholder="Enter a negative prompt",
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visible=False,
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)
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seed = gr.Slider(
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label="Seed",
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minimum=0,
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maximum=MAX_SEED,
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step=1,
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value=0,
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)
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randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
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with gr.Row():
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width = gr.Slider(
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label="Width",
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minimum=256,
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maximum=MAX_IMAGE_SIZE,
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step=32,
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value=1024, # Replace with defaults that work for your model
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)
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height = gr.Slider(
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label="Height",
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minimum=256,
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maximum=MAX_IMAGE_SIZE,
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step=32,
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value=1024, # Replace with defaults that work for your model
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)
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with gr.Row():
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guidance_scale = gr.Slider(
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label="Guidance scale",
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minimum=0.0,
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maximum=10.0,
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step=0.1,
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value=0.0, # Replace with defaults that work for your model
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)
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num_inference_steps = gr.Slider(
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label="Number of inference steps",
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minimum=1,
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maximum=50,
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step=1,
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value=2, # Replace with defaults that work for your model
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)
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gr.Examples(examples=examples, inputs=[prompt])
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gr.on(
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triggers=[generate_button.click],
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