update app.py

app.py

@@ -1,4 +1,3 @@
-# %%
 from typing import Optional, Tuple
 from einops import rearrange
 import torch
@@ -385,9 +384,8 @@ def main_fn(
     rgb = dont_use_too_much_green(rgb)
     return to_pil_images(rgb)
 
-
-default_images = ['/workspace/output/gradio/image_0.jpg', '/workspace/output/gradio/image_1.jpg', '/workspace/output/gradio/image_2.jpg', '/workspace/output/gradio/image_3.jpg', '/workspace/output/gradio/image_4.jpg', '/workspace/output/gradio/image_5.jpg']
-default_outputs = ['/workspace/output/gradio/ncut_0.jpg', '/workspace/output/gradio/ncut_1.jpg', '/workspace/output/gradio/ncut_2.jpg', '/workspace/output/gradio/ncut_3.jpg', '/workspace/output/gradio/ncut_4.jpg', '/workspace/output/gradio/ncut_5.jpg']
+default_images = ['./images/image_0.jpg', './images/image_1.jpg', './images/image_2.jpg', './images/image_3.jpg', './images/image_4.jpg', './images/image_5.jpg']
+default_outputs = ['./images/ncut_0.jpg', './images/ncut_1.jpg', './images/ncut_2.jpg', './images/ncut_3.jpg', './images/ncut_4.jpg', './images/ncut_5.jpg']
 
 demo = gr.Interface(
     main_fn,
@@ -410,61 +408,4 @@ demo = gr.Interface(
     ]
 )
 
-demo.launch(share=True)
-
-# %%
-
-
-# # %%
-# from ncut_pytorch import NCUT, rgb_from_tsne_3d
-
-# i_layer = -1
-# inp = block_outputs[i_layer]
-# eigvecs, eigvals = NCUT(
-#     num_eig=1000, num_sample=10000, device="cuda:0", affinity_focal_gamma=0.3, knn=10
-# ).fit_transform(inp.reshape(-1, inp.shape[-1]))
-# print(eigvecs.shape, eigvals.shape)
-# # %%
-# X_3d, rgb = rgb_from_tsne_3d(
-#     eigvecs[:, :100], num_sample=1000, perplexity=500, knn=10, seed=42
-# )
-# # %%
-# image_rgb = rgb.reshape(*inp.shape[:-1], 3)
-# # make sure the foval 20% of the image is red leading
-# x1, x2 = int(image_rgb.shape[1] * 0.4), int(image_rgb.shape[1] * 0.6)
-# y1, y2 = int(image_rgb.shape[2] * 0.4), int(image_rgb.shape[2] * 0.6)
-# sum_values = image_rgb[:, x1:x2, y1:y2].mean((0, 1, 2))
-# sorted_indices = sum_values.argsort(descending=True)
-# image_rgb = image_rgb[:, :, :, sorted_indices]
-
-# import matplotlib.pyplot as plt
-
-# fig, axes = plt.subplots(2, 3, figsize=(15, 10))
-# for i, ax in enumerate(axes.flat):
-#     ax.imshow(image_rgb[i])
-#     ax.axis("off")
-
-# %%
-save_dir = "/workspace/output/gradio"
-import os
-
-os.makedirs(save_dir, exist_ok=True)
-
-images = ['/workspace/guitars/lespual1.png', '/workspace/guitars/lespual2.png', '/workspace/guitars/lespual3.png', '/workspace/guitars/lespual4.png', '/workspace/guitars/lespual5.png', '/workspace/guitars/acoustic1.png']
-images = [Image.open(image).convert("RGB") for image in images]
-for i, image in enumerate(images):
-    image = image.resize((512, 512))
-    image.save(os.path.join(save_dir, f"image_{i}.jpg"), "JPEG", quality=70)
-# %%
-images = [(image, '') for image in images]
-image_rbg = main_fn(images)
-# %%
-for i, rgb in enumerate(image_rbg):
-    rgb = rgb.resize((512, 512), Image.NEAREST)
-    rgb.save(os.path.join(save_dir, f"ncut_{i}.jpg"), "JPEG", quality=70)
-# %%
-for i, rgb in enumerate(image_rgb):
-    rgb = Image.fromarray((rgb * 255).cpu().numpy().astype(np.uint8))
-    rgb.save(os.path.join(save_dir, f"ncut_{i}.png"))
-# %%
-%%
+demo.launch()