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Update app.py
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app.py
CHANGED
@@ -18,22 +18,22 @@ pipe, params = FlaxStableDiffusionControlNetPipeline.from_pretrained(
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"runwayml/stable-diffusion-v1-5", controlnet=controlnet, revision="flax", dtype=jnp.bfloat16
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)
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def infer(
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params["controlnet"] = controlnet_params
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num_samples = 1 #jax.device_count()
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rng = create_key(0)
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rng = jax.random.split(rng, jax.device_count())
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prompt_ids = pipe.prepare_text_inputs([prompts] * num_samples)
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negative_prompt_ids = pipe.prepare_text_inputs([negative_prompts] * num_samples)
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processed_image = pipe.prepare_image_inputs([
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p_params = replicate(params)
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prompt_ids = shard(prompt_ids)
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negative_prompt_ids = shard(negative_prompt_ids)
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processed_image = shard(processed_image)
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output = pipe(
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@@ -42,7 +42,7 @@ def infer(prompts, negative_prompts, image):
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params=p_params,
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prng_seed=rng,
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num_inference_steps=50,
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neg_prompt_ids=negative_prompt_ids,
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jit=True,
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).images
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@@ -52,7 +52,7 @@ def infer(prompts, negative_prompts, image):
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#gr.Interface(infer, inputs=["text", "text", "image"], outputs="gallery").launch()
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title = "Animal Pose Control Net"
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description = "This is a demo
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with gr.Blocks(theme=gr.themes.Default(font=[gr.themes.GoogleFont("Inconsolata"), "Arial", "sans-serif"])) as demo:
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gr.Markdown(
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@@ -68,7 +68,6 @@ gr.Examples(
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["a tortoiseshell cat is sitting on a cushion", "https://huggingface.co/JFoz/dog-cat-pose/blob/main/images_0.png"],
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["a yellow dog standing on a lawn", "https://huggingface.co/JFoz/dog-cat-pose/blob/main/images_1.png"],
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]
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cache_examples=True,
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)
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gr.Interface(fn = infer, inputs = ["text", "text", "image"], outputs = "image",
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"runwayml/stable-diffusion-v1-5", controlnet=controlnet, revision="flax", dtype=jnp.bfloat16
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)
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def infer(prompt, image):
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params["controlnet"] = controlnet_params
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num_samples = 1 #jax.device_count()
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rng = create_key(0)
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rng = jax.random.split(rng, jax.device_count())
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im = image
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image = Image.fromarray(im)
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#prompt_ids = pipe.prepare_text_inputs([prompts] * num_samples)
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#negative_prompt_ids = pipe.prepare_text_inputs([negative_prompts] * num_samples)
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processed_image = pipe.prepare_image_inputs([image] * num_samples)
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p_params = replicate(params)
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#prompt_ids = shard(prompt_ids)
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#negative_prompt_ids = shard(negative_prompt_ids)
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processed_image = shard(processed_image)
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output = pipe(
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params=p_params,
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prng_seed=rng,
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num_inference_steps=50,
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#neg_prompt_ids=negative_prompt_ids,
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jit=True,
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).images
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#gr.Interface(infer, inputs=["text", "text", "image"], outputs="gallery").launch()
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title = "Animal Pose Control Net"
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description = "This is a demo of Animal Pose ControlNet, which is a model trained on runwayml/stable-diffusion-v1-5 with new type of conditioning."
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with gr.Blocks(theme=gr.themes.Default(font=[gr.themes.GoogleFont("Inconsolata"), "Arial", "sans-serif"])) as demo:
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gr.Markdown(
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["a tortoiseshell cat is sitting on a cushion", "https://huggingface.co/JFoz/dog-cat-pose/blob/main/images_0.png"],
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["a yellow dog standing on a lawn", "https://huggingface.co/JFoz/dog-cat-pose/blob/main/images_1.png"],
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]
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)
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gr.Interface(fn = infer, inputs = ["text", "text", "image"], outputs = "image",
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