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Update app.py
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app.py
CHANGED
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@@ -14,6 +14,7 @@ from IP_Adapter.ip_adapter import IPAdapter
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# Paths and device
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base_model_path = "stable-diffusion-v1-5/stable-diffusion-v1-5"
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vae_model_path = "stabilityai/sd-vae-ft-mse"
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image_encoder_path = "IP_Adapter/ip_adapter/models/image_encoder/"
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ip_ckpt = "IP_Adapter/ip_adapter/models/ip-adapter_sd15.bin"
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device = "cpu" # or "cuda" if using GPU
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@@ -47,7 +48,7 @@ def generate_variations(upload_img):
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safety_checker=None,
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torch_dtype=torch.float16
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)
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ip_model = IPAdapter(pipe,
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images = ip_model.generate(pil_image=upload_img, num_samples=4, num_inference_steps=50, seed=42)
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return image_grid(images, 1, 4)
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@@ -60,7 +61,7 @@ def generate_img2img(base_img, guide_img):
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feature_extractor=None,
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safety_checker=None
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)
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ip_model = IPAdapter(pipe,
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images = ip_model.generate(pil_image=base_img, image=guide_img, strength=0.6, num_samples=4, num_inference_steps=50, seed=42)
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return image_grid(images, 1, 4)
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@@ -73,7 +74,7 @@ def generate_inpaint(input_img, masked_img, mask_img):
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feature_extractor=None,
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safety_checker=None
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)
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ip_model = IPAdapter(pipe,
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images = ip_model.generate(pil_image=input_img, image=masked_img, mask_image=mask_img,
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strength=0.7, num_samples=4, num_inference_steps=50, seed=42)
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return image_grid(images, 1, 4)
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# Paths and device
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base_model_path = "stable-diffusion-v1-5/stable-diffusion-v1-5"
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vae_model_path = "stabilityai/sd-vae-ft-mse"
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image_encoder_repo="InvokeAI/ip_adapter_sd_image_encoder"
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image_encoder_path = "IP_Adapter/ip_adapter/models/image_encoder/"
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ip_ckpt = "IP_Adapter/ip_adapter/models/ip-adapter_sd15.bin"
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device = "cpu" # or "cuda" if using GPU
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safety_checker=None,
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torch_dtype=torch.float16
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)
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ip_model = IPAdapter(pipe, image_encoder_repo, ip_ckpt, device)
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images = ip_model.generate(pil_image=upload_img, num_samples=4, num_inference_steps=50, seed=42)
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return image_grid(images, 1, 4)
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feature_extractor=None,
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safety_checker=None
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)
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ip_model = IPAdapter(pipe, image_encoder_repo, ip_ckpt, device)
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images = ip_model.generate(pil_image=base_img, image=guide_img, strength=0.6, num_samples=4, num_inference_steps=50, seed=42)
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return image_grid(images, 1, 4)
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feature_extractor=None,
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safety_checker=None
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)
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ip_model = IPAdapter(pipe, image_encoder_repo, ip_ckpt, device)
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images = ip_model.generate(pil_image=input_img, image=masked_img, mask_image=mask_img,
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strength=0.7, num_samples=4, num_inference_steps=50, seed=42)
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return image_grid(images, 1, 4)
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