Spaces:
Running
on
Zero
Running
on
Zero
Commit
•
1287e5e
1
Parent(s):
0e80ee6
Update app.py
Browse files
app.py
CHANGED
@@ -49,18 +49,20 @@ def generate_image(images, prompt, negative_prompt, preserve_face_structure, pro
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faces = app.get(face)
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faceid_embed = torch.from_numpy(faces[0].normed_embedding).unsqueeze(0)
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faceid_all_embeds.append(faceid_embed)
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-
if(first_iteration):
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face_image = face_align.norm_crop(face, landmark=faces[0].kps, image_size=224) # you can also segment the face
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first_iteration = False
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average_embedding = torch.mean(torch.stack(faceid_all_embeds, dim=0), dim=0)
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if(not preserve_face_structure):
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image = ip_model.generate(
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prompt=prompt, negative_prompt=negative_prompt, faceid_embeds=average_embedding,
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width=512, height=512, num_inference_steps=30
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)
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else:
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image = ip_model_plus.generate(
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prompt=prompt, negative_prompt=negative_prompt, faceid_embeds=average_embedding,
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face_image=face_image, shortcut=True, s_scale=1.5, width=512, height=512, num_inference_steps=30
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faces = app.get(face)
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faceid_embed = torch.from_numpy(faces[0].normed_embedding).unsqueeze(0)
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faceid_all_embeds.append(faceid_embed)
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+
if(first_iteration and preserve_face_structure):
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face_image = face_align.norm_crop(face, landmark=faces[0].kps, image_size=224) # you can also segment the face
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first_iteration = False
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average_embedding = torch.mean(torch.stack(faceid_all_embeds, dim=0), dim=0)
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if(not preserve_face_structure):
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+
print("Generating normal")
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image = ip_model.generate(
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prompt=prompt, negative_prompt=negative_prompt, faceid_embeds=average_embedding,
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width=512, height=512, num_inference_steps=30
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)
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else:
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+
print("Generating plus")
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image = ip_model_plus.generate(
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prompt=prompt, negative_prompt=negative_prompt, faceid_embeds=average_embedding,
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face_image=face_image, shortcut=True, s_scale=1.5, width=512, height=512, num_inference_steps=30
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