Upload imagedream/camera_utils.py with huggingface_hub

imagedream/camera_utils.py

@@ -1,99 +1,99 @@
-import numpy as np
-import torch
-
-
-def create_camera_to_world_matrix(elevation, azimuth):
-    elevation = np.radians(elevation)
-    azimuth = np.radians(azimuth)
-    # Convert elevation and azimuth angles to Cartesian coordinates on a unit sphere
-    x = np.cos(elevation) * np.sin(azimuth)
-    y = np.sin(elevation)
-    z = np.cos(elevation) * np.cos(azimuth)
-
-    # Calculate camera position, target, and up vectors
-    camera_pos = np.array([x, y, z])
-    target = np.array([0, 0, 0])
-    up = np.array([0, 1, 0])
-
-    # Construct view matrix
-    forward = target - camera_pos
-    forward /= np.linalg.norm(forward)
-    right = np.cross(forward, up)
-    right /= np.linalg.norm(right)
-    new_up = np.cross(right, forward)
-    new_up /= np.linalg.norm(new_up)
-    cam2world = np.eye(4)
-    cam2world[:3, :3] = np.array([right, new_up, -forward]).T
-    cam2world[:3, 3] = camera_pos
-    return cam2world
-
-
-def convert_opengl_to_blender(camera_matrix):
-    if isinstance(camera_matrix, np.ndarray):
-        # Construct transformation matrix to convert from OpenGL space to Blender space
-        flip_yz = np.array([[1, 0, 0, 0], [0, 0, -1, 0], [0, 1, 0, 0], [0, 0, 0, 1]])
-        camera_matrix_blender = np.dot(flip_yz, camera_matrix)
-    else:
-        # Construct transformation matrix to convert from OpenGL space to Blender space
-        flip_yz = torch.tensor(
-            [[1, 0, 0, 0], [0, 0, -1, 0], [0, 1, 0, 0], [0, 0, 0, 1]]
-        )
-        if camera_matrix.ndim == 3:
-            flip_yz = flip_yz.unsqueeze(0)
-        camera_matrix_blender = torch.matmul(flip_yz.to(camera_matrix), camera_matrix)
-    return camera_matrix_blender
-
-
-def normalize_camera(camera_matrix):
-    """normalize the camera location onto a unit-sphere"""
-    if isinstance(camera_matrix, np.ndarray):
-        camera_matrix = camera_matrix.reshape(-1, 4, 4)
-        translation = camera_matrix[:, :3, 3]
-        translation = translation / (
-            np.linalg.norm(translation, axis=1, keepdims=True) + 1e-8
-        )
-        camera_matrix[:, :3, 3] = translation
-    else:
-        camera_matrix = camera_matrix.reshape(-1, 4, 4)
-        translation = camera_matrix[:, :3, 3]
-        translation = translation / (
-            torch.norm(translation, dim=1, keepdim=True) + 1e-8
-        )
-        camera_matrix[:, :3, 3] = translation
-    return camera_matrix.reshape(-1, 16)
-
-
-def get_camera(
-    num_frames, 
-    elevation=15, 
-    azimuth_start=0, 
-    azimuth_span=360, 
-    blender_coord=True,
-    extra_view=False,
-):
-    angle_gap = azimuth_span / num_frames
-    cameras = []
-    for azimuth in np.arange(azimuth_start, azimuth_span + azimuth_start, angle_gap):
-        camera_matrix = create_camera_to_world_matrix(elevation, azimuth)
-        if blender_coord:
-            camera_matrix = convert_opengl_to_blender(camera_matrix)
-        cameras.append(camera_matrix.flatten())
-        
-    if extra_view:
-        dim = len(cameras[0])
-        cameras.append(np.zeros(dim))  
-    return torch.tensor(np.stack(cameras, 0)).float()
-
-
-def get_camera_for_index(data_index):
-    """
-    按照当前我们的数据格式, 以000为正对我们的情况:
-    000是正面, ev: 0, azimuth: 0
-    001是左边, ev: 0, azimuth: -90
-    002是下面, ev: -90, azimuth: 0
-    003是背面, ev: 0, azimuth: 180
-    004是右边, ev: 0, azimuth: 90
-    005是上面, ev: 90, azimuth: 0
-    """
-    params = [(0, 0), (0, -90), (-90, 0), (0, 180), (0, 90), (90, 0)]
+import numpy as np
+import torch
+
+
+def create_camera_to_world_matrix(elevation, azimuth):
+    elevation = np.radians(elevation)
+    azimuth = np.radians(azimuth)
+    # Convert elevation and azimuth angles to Cartesian coordinates on a unit sphere
+    x = np.cos(elevation) * np.sin(azimuth)
+    y = np.sin(elevation)
+    z = np.cos(elevation) * np.cos(azimuth)
+
+    # Calculate camera position, target, and up vectors
+    camera_pos = np.array([x, y, z])
+    target = np.array([0, 0, 0])
+    up = np.array([0, 1, 0])
+
+    # Construct view matrix
+    forward = target - camera_pos
+    forward /= np.linalg.norm(forward)
+    right = np.cross(forward, up)
+    right /= np.linalg.norm(right)
+    new_up = np.cross(right, forward)
+    new_up /= np.linalg.norm(new_up)
+    cam2world = np.eye(4)
+    cam2world[:3, :3] = np.array([right, new_up, -forward]).T
+    cam2world[:3, 3] = camera_pos
+    return cam2world
+
+
+def convert_opengl_to_blender(camera_matrix):
+    if isinstance(camera_matrix, np.ndarray):
+        # Construct transformation matrix to convert from OpenGL space to Blender space
+        flip_yz = np.array([[1, 0, 0, 0], [0, 0, -1, 0], [0, 1, 0, 0], [0, 0, 0, 1]])
+        camera_matrix_blender = np.dot(flip_yz, camera_matrix)
+    else:
+        # Construct transformation matrix to convert from OpenGL space to Blender space
+        flip_yz = torch.tensor(
+            [[1, 0, 0, 0], [0, 0, -1, 0], [0, 1, 0, 0], [0, 0, 0, 1]]
+        )
+        if camera_matrix.ndim == 3:
+            flip_yz = flip_yz.unsqueeze(0)
+        camera_matrix_blender = torch.matmul(flip_yz.to(camera_matrix), camera_matrix)
+    return camera_matrix_blender
+
+
+def normalize_camera(camera_matrix):
+    """normalize the camera location onto a unit-sphere"""
+    if isinstance(camera_matrix, np.ndarray):
+        camera_matrix = camera_matrix.reshape(-1, 4, 4)
+        translation = camera_matrix[:, :3, 3]
+        translation = translation / (
+            np.linalg.norm(translation, axis=1, keepdims=True) + 1e-8
+        )
+        camera_matrix[:, :3, 3] = translation
+    else:
+        camera_matrix = camera_matrix.reshape(-1, 4, 4)
+        translation = camera_matrix[:, :3, 3]
+        translation = translation / (
+            torch.norm(translation, dim=1, keepdim=True) + 1e-8
+        )
+        camera_matrix[:, :3, 3] = translation
+    return camera_matrix.reshape(-1, 16)
+
+
+def get_camera(
+    num_frames, 
+    elevation=15, 
+    azimuth_start=0, 
+    azimuth_span=360, 
+    blender_coord=True,
+    extra_view=False,
+):
+    angle_gap = azimuth_span / num_frames
+    cameras = []
+    for azimuth in np.arange(azimuth_start, azimuth_span + azimuth_start, angle_gap):
+        camera_matrix = create_camera_to_world_matrix(elevation, azimuth)
+        if blender_coord:
+            camera_matrix = convert_opengl_to_blender(camera_matrix)
+        cameras.append(camera_matrix.flatten())
+        
+    if extra_view:
+        dim = len(cameras[0])
+        cameras.append(np.zeros(dim))  
+    return torch.tensor(np.stack(cameras, 0)).float()
+
+
+def get_camera_for_index(data_index):
+    """
+    按照当前我们的数据格式, 以000为正对我们的情况:
+    000是正面, ev: 0, azimuth: 0
+    001是左边, ev: 0, azimuth: -90
+    002是下面, ev: -90, azimuth: 0
+    003是背面, ev: 0, azimuth: 180
+    004是右边, ev: 0, azimuth: 90
+    005是上面, ev: 90, azimuth: 0
+    """
+    params = [(0, 0), (0, -90), (-90, 0), (0, 180), (0, 90), (90, 0)]
     return get_camera(1, *params[data_index])