Update app.py
Browse files
app.py
CHANGED
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@@ -36,9 +36,6 @@ def create_key(seed=0):
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return jax.random.PRNGKey(seed)
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rng = create_key(0)
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def canny_filter(image):
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@@ -48,19 +45,21 @@ def canny_filter(image):
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edges_image = cv2.Canny(blurred_image, 50, 150)
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return edges_image
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def infer(prompts, negative_prompts, image):
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# load control net and stable diffusion v1-5
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controlnet, controlnet_params = FlaxControlNetModel.from_pretrained(
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"jax-diffusers-event/canny-coyo1m", dtype=jnp.float32
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)
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pipe, params = FlaxStableDiffusionControlNetPipeline.from_pretrained(
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"runwayml/stable-diffusion-v1-5", controlnet=controlnet, from_pt=True, dtype=jnp.float32
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)
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params["controlnet"] = controlnet_params
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num_samples = jax.device_count()
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rng = jax.random.split(rng, jax.device_count())
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canny_image = canny_filter(image)
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return jax.random.PRNGKey(seed)
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def canny_filter(image):
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edges_image = cv2.Canny(blurred_image, 50, 150)
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return edges_image
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# load control net and stable diffusion v1-5
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controlnet, controlnet_params = FlaxControlNetModel.from_pretrained(
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"jax-diffusers-event/canny-coyo1m", dtype=jnp.float32
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)
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pipe, params = FlaxStableDiffusionControlNetPipeline.from_pretrained(
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"runwayml/stable-diffusion-v1-5", controlnet=controlnet, from_pt=True, dtype=jnp.float32
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)
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def infer(prompts, negative_prompts, image):
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params["controlnet"] = controlnet_params
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num_samples = 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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canny_image = canny_filter(image)
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