Update app.py
Browse files
app.py
CHANGED
@@ -7,7 +7,7 @@ from huggingface_hub import login, HfApi, HfFolder
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from PIL import Image
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import os
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from datetime import datetime
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-
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# Get your Hugging Face API token
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folder = HfFolder()
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@@ -33,27 +33,31 @@ pipe2.enable_xformers_memory_efficient_attention()
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def save_image_to_hf_space(image_np, image_name):
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# Name of your Hugging Face repo
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repo_name = "FFusion/
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# Convert the numpy array to an image
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image = Image.fromarray(image_np.astype('uint8'))
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# Append a timestamp to the filename
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timestamp = datetime.now().strftime("%Y%m%d-%H%M%S")
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image_name_with_timestamp = f"{image_name}-{timestamp}"
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# Save the image locally
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image.save(
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# Upload the image to your Hugging Face repo
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api.upload_file(
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token=token,
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path_or_fileobj=
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repo_id=repo_name,
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)
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def genie (prompt, negative_prompt, scale, steps, seed):
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torch.cuda.empty_cache()
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@@ -65,8 +69,8 @@ def genie (prompt, negative_prompt, scale, steps, seed):
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refined_image_np = np.array(refined_images[0])
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# Save the generated images to Hugging Face Spaces
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return int_image_np, refined_image_np
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from PIL import Image
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import os
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from datetime import datetime
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import shutil
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# Get your Hugging Face API token
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folder = HfFolder()
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def save_image_to_hf_space(image_np, image_name):
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# Name of your Hugging Face repo
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repo_name = "FFusion/FF2"
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# Convert the numpy array to an image
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image = Image.fromarray(image_np.astype('uint8'))
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# Append a timestamp to the filename
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timestamp = datetime.now().strftime("%Y%m%d-%H%M%S")
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image_name_with_timestamp = f"{image_name}-{timestamp}.png"
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# Save the image locally
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local_image_path = f"./{image_name_with_timestamp}"
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image.save(local_image_path)
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# Upload the image to your Hugging Face repo
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api.upload_file(
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token=token,
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path_or_fileobj=local_image_path,
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repo_id=repo_name,
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path_in_repo=image_name_with_timestamp # The path where the image will be stored in the repository
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)
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# Save the image to the persistent storage
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persistent_storage_path = f"/data/{image_name_with_timestamp}"
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shutil.copy(local_image_path, persistent_storage_path)
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def genie (prompt, negative_prompt, scale, steps, seed):
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torch.cuda.empty_cache()
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refined_image_np = np.array(refined_images[0])
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# Save the generated images to Hugging Face Spaces
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save_image_to_hf_space(int_image_np, "int_image")
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save_image_to_hf_space(refined_image_np, "refined_image")
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return int_image_np, refined_image_np
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