use issue#1 as gallery
Browse files- assets/gallery.md +0 -0
- encoding.py +0 -4
- main_nerf.py +1 -1
- nerf/provider.py +1 -1
- readme.md +1 -1
assets/gallery.md
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encoding.py
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@@ -26,10 +26,6 @@ def get_encoder(encoding, input_dim=3,
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elif encoding == 'tiledgrid':
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from gridencoder import GridEncoder
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encoder = GridEncoder(input_dim=input_dim, num_levels=num_levels, level_dim=level_dim, base_resolution=base_resolution, log2_hashmap_size=log2_hashmap_size, desired_resolution=desired_resolution, gridtype='tiled', align_corners=align_corners)
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elif encoding == 'ash':
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from ashencoder import AshEncoder
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encoder = AshEncoder(input_dim=input_dim, output_dim=16, log2_hashmap_size=log2_hashmap_size, resolution=desired_resolution)
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else:
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raise NotImplementedError('Unknown encoding mode, choose from [None, frequency, sphere_harmonics, hashgrid, tiledgrid]')
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elif encoding == 'tiledgrid':
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from gridencoder import GridEncoder
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encoder = GridEncoder(input_dim=input_dim, num_levels=num_levels, level_dim=level_dim, base_resolution=base_resolution, log2_hashmap_size=log2_hashmap_size, desired_resolution=desired_resolution, gridtype='tiled', align_corners=align_corners)
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else:
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raise NotImplementedError('Unknown encoding mode, choose from [None, frequency, sphere_harmonics, hashgrid, tiledgrid]')
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main_nerf.py
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@@ -96,7 +96,7 @@ if __name__ == '__main__':
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else:
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test_loader = NeRFDataset(opt, device=device, type='test', H=opt.H, W=opt.W, size=100).dataloader()
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trainer.test(test_loader)
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trainer.save_mesh(resolution=256)
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else:
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else:
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test_loader = NeRFDataset(opt, device=device, type='test', H=opt.H, W=opt.W, size=100).dataloader()
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trainer.test(test_loader)
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# trainer.save_mesh(resolution=256)
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else:
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nerf/provider.py
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@@ -169,7 +169,7 @@ class NeRFDataset:
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else:
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# circle pose
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phi = (index[0] / self.size) * 2 * np.pi
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poses, dirs = circle_poses(self.device, return_dirs=self.opt.dir_text, radius=self.radius_range[1], theta=np.pi/
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# fixed focal
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fov = (self.fovy_range[1] + self.fovy_range[0]) / 2
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else:
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# circle pose
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phi = (index[0] / self.size) * 2 * np.pi
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poses, dirs = circle_poses(self.device, return_dirs=self.opt.dir_text, radius=self.radius_range[1] * 1.2, theta=np.pi/3, phi=phi)
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# fixed focal
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fov = (self.fovy_range[1] + self.fovy_range[0]) / 2
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readme.md
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@@ -8,7 +8,7 @@ Examples generated from text prompt `a DSLR photo of a pineapple` viewed with th
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https://user-images.githubusercontent.com/25863658/194241493-f3e68f78-aefe-479e-a4a8-001424a61b37.mp4
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### [Gallery](
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# Important Notice
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This project is a **work-in-progress**, and contains lots of differences from the paper. Also, many features are still not implemented now. **The current generation quality cannot match the results from the original paper, and still fail badly for many prompts.**
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https://user-images.githubusercontent.com/25863658/194241493-f3e68f78-aefe-479e-a4a8-001424a61b37.mp4
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### [Gallery](https://github.com/ashawkey/stable-dreamfusion/issues/1) | [Update Logs](assets/update_logs.md)
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# Important Notice
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This project is a **work-in-progress**, and contains lots of differences from the paper. Also, many features are still not implemented now. **The current generation quality cannot match the results from the original paper, and still fail badly for many prompts.**
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