Spaces:
Build error
Build error
Multi prompts feature
Browse files
zoom.py
CHANGED
@@ -16,26 +16,25 @@ inpaint_model_list = [
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default_prompt = "A psychedelic jungle with trees that have glowing, fractal-like patterns, Simon stalenhag poster 1920s style, street level view, hyper futuristic, 8k resolution, hyper realistic"
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default_negative_prompt = "frames, borderline, text, charachter, duplicate, error, out of frame, watermark, low quality, ugly, deformed, blur"
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# TODO:
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# prompts = {
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# 0: "prompt1",
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# 7: "prompt2"
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# }
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custom_init_image = False
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init_image_address = "/init/image.jpeg"
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def zoom(
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model_id,
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negative_prompt,
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num_outpainting_steps,
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guidance_scale,
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num_inference_steps,
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custom_init_image
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):
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pipe = StableDiffusionInpaintPipeline.from_pretrained(
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model_id,
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torch_dtype=torch.float16,
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@@ -57,18 +56,19 @@ def zoom(
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mask_image = np.array(current_image)[:, :, 3]
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mask_image = Image.fromarray(255-mask_image).convert("RGB")
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current_image = current_image.convert("RGB")
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if(custom_init_image):
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else:
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mask_width = 128
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num_interpol_frames = 30
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@@ -91,7 +91,7 @@ def zoom(
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# inpainting step
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current_image = current_image.convert("RGB")
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images = pipe(prompt=
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negative_prompt=negative_prompt,
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image=current_image,
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guidance_scale=guidance_scale,
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@@ -125,8 +125,8 @@ def zoom(
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interpol_image.paste(prev_image_fix_crop, mask=prev_image_fix_crop)
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all_frames.append(interpol_image)
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all_frames.append(current_image)
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video_file_name = "infinite_zoom_" + str(time.time())
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fps = 30
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save_path = video_file_name + ".mp4"
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@@ -137,15 +137,20 @@ def zoom(
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start_frame_dupe_amount, last_frame_dupe_amount)
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return save_path
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def zoom_app():
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with gr.Blocks():
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with gr.Row():
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with gr.Column():
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)
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outpaint_negative_prompt = gr.Textbox(
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@@ -185,7 +190,7 @@ def zoom_app():
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)
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init_image = gr.Image(type="pil")
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generate_btn = gr.Button(value='Generate video')
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with gr.Column():
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output_image = gr.Video(label='Output', format="mp4").style(
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width=512, height=512)
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@@ -194,7 +199,7 @@ def zoom_app():
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fn=zoom,
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inputs=[
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model_id,
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outpaint_negative_prompt,
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outpaint_steps,
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guidance_scale,
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]
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default_prompt = "A psychedelic jungle with trees that have glowing, fractal-like patterns, Simon stalenhag poster 1920s style, street level view, hyper futuristic, 8k resolution, hyper realistic"
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default_negative_prompt = "frames, borderline, text, charachter, duplicate, error, out of frame, watermark, low quality, ugly, deformed, blur"
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def zoom(
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model_id,
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prompts_array,
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negative_prompt,
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num_outpainting_steps,
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guidance_scale,
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num_inference_steps,
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custom_init_image
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):
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prompts = {}
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for x in prompts_array:
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try:
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key = int(x[0])
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value = str(x[1])
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prompts[key] = value
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except ValueError:
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pass
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pipe = StableDiffusionInpaintPipeline.from_pretrained(
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model_id,
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torch_dtype=torch.float16,
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mask_image = np.array(current_image)[:, :, 3]
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mask_image = Image.fromarray(255-mask_image).convert("RGB")
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current_image = current_image.convert("RGB")
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if (custom_init_image):
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current_image = custom_init_image.resize(
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(width, height), resample=Image.LANCZOS)
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else:
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init_images = pipe(prompt=prompts[min(k for k in prompts.keys() if k >= 0)],
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negative_prompt=negative_prompt,
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image=current_image,
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guidance_scale=guidance_scale,
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height=height,
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width=width,
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mask_image=mask_image,
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num_inference_steps=num_inference_steps)[0]
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current_image = init_images[0]
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mask_width = 128
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num_interpol_frames = 30
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# inpainting step
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current_image = current_image.convert("RGB")
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images = pipe(prompt=prompts[max(k for k in prompts.keys() if k <= i)],
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negative_prompt=negative_prompt,
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image=current_image,
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guidance_scale=guidance_scale,
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interpol_image.paste(prev_image_fix_crop, mask=prev_image_fix_crop)
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all_frames.append(interpol_image)
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all_frames.append(current_image)
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# interpol_image.show()
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video_file_name = "infinite_zoom_" + str(time.time())
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fps = 30
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save_path = video_file_name + ".mp4"
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start_frame_dupe_amount, last_frame_dupe_amount)
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return save_path
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+
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def zoom_app():
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with gr.Blocks():
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with gr.Row():
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with gr.Column():
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outpaint_prompts = gr.Dataframe(
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type="array",
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headers=["outpaint steps", "prompt"],
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datatype=["number", "str"],
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row_count=1,
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col_count=(2, "fixed"),
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value=[[0, default_prompt]],
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wrap=True
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)
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outpaint_negative_prompt = gr.Textbox(
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)
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init_image = gr.Image(type="pil")
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generate_btn = gr.Button(value='Generate video')
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with gr.Column():
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output_image = gr.Video(label='Output', format="mp4").style(
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width=512, height=512)
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fn=zoom,
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inputs=[
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model_id,
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outpaint_prompts,
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outpaint_negative_prompt,
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outpaint_steps,
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guidance_scale,
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