img to rgb
Browse files
README.md
CHANGED
@@ -67,17 +67,19 @@ from huggingface_hub import hf_hub_download
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# This is an example image we provide
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path = hf_hub_download(repo_id="StonyBrook-CVLab/PixCell-256", filename="test_image.png")
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image = Image.open(path)
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# Extract UNI embedding from the image
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uni_inp = transform(image).unsqueeze(dim=0)
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with torch.inference_mode():
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uni_emb = uni_model(uni_inp.to(device))
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print("Extracted UNI:", uni_emb.shape)
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# Get unconditional embedding for classifier-free guidance
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uncond = pipeline.get_unconditional_embedding(uni_emb.shape[0])
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# Generate new samples
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samples = pipeline(uni_embeds=uni_emb, negative_uni_embeds=uncond, guidance_scale=3., num_images_per_prompt=1)
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```
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# This is an example image we provide
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path = hf_hub_download(repo_id="StonyBrook-CVLab/PixCell-256", filename="test_image.png")
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image = Image.open(path).convert("RGB")
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# Extract UNI embedding from the image
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uni_inp = transform(image).unsqueeze(dim=0)
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with torch.inference_mode():
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uni_emb = uni_model(uni_inp.to(device))
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# reshape UNI to (bs, 1, D)
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uni_emb = uni_emb.unsqueeze(1)
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print("Extracted UNI:", uni_emb.shape)
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# Get unconditional embedding for classifier-free guidance
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uncond = pipeline.get_unconditional_embedding(uni_emb.shape[0])
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# Generate new samples
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samples = pipeline(uni_embeds=uni_emb, negative_uni_embeds=uncond, guidance_scale=3., num_images_per_prompt=1).images
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```
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