pose encoder model
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@@ -35,14 +35,14 @@ class PoseRenderer(Module):
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super().__init__()
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colors = np.load('custom_data/pose_colors.npy')
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self.textures = TexturesVertex(verts_features=torch.from_numpy(colors).to(device)[None, :, :])
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self.cam = torch.tensor([5.0, 0.0, 0.0], device=device).cpu().numpy()
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self.cam = torch.tensor([3.0, 0.0, 0.0], device=device).cpu().numpy()
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def forward(self, verts: torch.Tensor, faces: torch.Tensor):
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cameras, K = get_camera(self.cam, [480, 640], verts.get_device())
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cameras, K = get_camera(self.cam, [512, 512], verts.get_device(), res_x=512, res_y=512)
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raster_settings = RasterizationSettings(
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image_size=(480, 640),
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image_size=(512, 512),
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blur_radius=0.0,
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faces_per_pixel=1,
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bin_size=0
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@@ -63,7 +63,7 @@ if __name__ == '__main__':
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smpl = SMPL(path='superSMPL', device='cuda')
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pose = torch.zeros((1,72), device='cuda')
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# generate random pose
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pose[:,3:] = torch.randn((1,69), device='cuda') * 0.1
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# pose[:,3:] = torch.randn((1,69), device='cuda') * 0.1
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body, _ = smpl(pose, torch.zeros((1,11), device='cuda'), remove=False)
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colors = np.zeros((body.shape[1], 3))
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