Upload 6 files

load_dataset.py

@@ -30,6 +30,7 @@ from utils import *
 # 1. Load scenes infomation
 # --------------------------------------------------------------------------
 dataset_root = 'root_path/360Motion-Dataset'
+video_res = '480_720'
 video_names = []
 scenes = ['Desert', 'HDRI']
 scene_location_pair = {
@@ -44,7 +45,7 @@ scene_location_pair = {
     }
 }
 for scene in scenes:
-    video_path = os.path.join(dataset_root, scene)
+    video_path = os.path.join(dataset_root, video_res, scene)
     locations_path = os.path.join(video_path, "location_data.json")
     with open(locations_path, 'r') as f: locations = json.load(f)
     locations_info = {locations[idx]['name']:locations[idx] for idx in range(len(locations))}
@@ -54,7 +55,7 @@ for scene in scenes:
                 location = scene_location_pair[scene]
             else:
                 location = scene_location_pair['HDRI'][video_name.split('_')[1]]
-            video_names.append((scene, video_name, location, locations_info))
+            video_names.append((video_res, scene, video_name, location, locations_info))
 
 # --------------------------------------------------------------------------
 # 2. Load 12 surrounding cameras
@@ -81,9 +82,9 @@ sample_n_frames = 49
 # --------------------------------------------------------------------------
 # 3. Load a sample of video & object poses
 # --------------------------------------------------------------------------
-(scene, video_name, location, locations_info) = video_names[20]
+(video_res, scene, video_name, location, locations_info) = video_names[20]
 
-with open(os.path.join(dataset_root, scene, video_name, video_name+'.json'), 'r') as f: objs_file = json.load(f)
+with open(os.path.join(dataset_root, video_res, scene, video_name, video_name+'.json'), 'r') as f: objs_file = json.load(f)
 objs_num = len(objs_file['0'])
 video_index = random.randint(1, cam_num-1)
 
@@ -131,7 +132,7 @@ start_frame_ind = random.randint(10, max(10, total_frames - cropped_length - 1))
 end_frame_ind = min(start_frame_ind + cropped_length, total_frames)
 frame_indices = np.linspace(start_frame_ind, end_frame_ind - 1, sample_n_frames, dtype=int)
 
-video_frames_path = os.path.join(dataset_root, scene, video_name, 'videos', video_name+ f'_C_{video_index:02d}_35mm.mp4')
+video_frames_path = os.path.join(dataset_root, video_res, scene, video_name, 'videos', video_name+ f'_C_{video_index:02d}_35mm.mp4')
 cap = cv2.VideoCapture(video_frames_path)
 height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
 width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))

traj_vis/D_loc1_61_t3n13_003d_Hemi12_1.json

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traj_vis/Hemi12_transforms.json

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+}

traj_vis/location_data_desert.json

@@ -0,0 +1,287 @@
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+                ],
+                "rotation": [
+                    0.0,
+                    0.0,
+                    0.0
+                ],
+                "scale": [
+                    1.0,
+                    1.0,
+                    1.0
+                ]
+            }
+        },
+        "Height": "H10"
+    }
+]

utils.py

@@ -19,10 +19,93 @@ import os
 import numpy as np
 from io import BytesIO
 import imageio.v2 as imageio
-import open3d
+import open3d as o3d
 import math
-from tools.vis_cam import get_camera_frustum, frustums2lineset
 import trimesh
+import json
+
+
+def get_camera_frustum(img_size, K, W2C, frustum_length=0.5, color=[0., 1., 0.]):
+    W, H = img_size
+    hfov = np.rad2deg(np.arctan(W / 2. / K[0, 0]) * 2.)
+    vfov = np.rad2deg(np.arctan(H / 2. / K[1, 1]) * 2.)
+    half_w = frustum_length * np.tan(np.deg2rad(hfov / 2.))
+    half_h = frustum_length * np.tan(np.deg2rad(vfov / 2.))
+
+    # build view frustum for camera (I, 0)
+    frustum_points = np.array([[0., 0., 0.],                          # frustum origin
+                               [-half_w, -half_h, frustum_length],    # top-left image corner
+                               [half_w, -half_h, frustum_length],     # top-right image corner
+                               [half_w, half_h, frustum_length],      # bottom-right image corner
+                               [-half_w, half_h, frustum_length]])    # bottom-left image corner
+    frustum_lines = np.array([[0, i] for i in range(1, 5)] + [[i, (i+1)] for i in range(1, 4)] + [[4, 1]])
+    frustum_colors = np.tile(np.array(color).reshape((1, 3)), (frustum_lines.shape[0], 1))
+
+    # frustum_colors = np.vstack((np.tile(np.array([[1., 0., 0.]]), (4, 1)),
+    #                            np.tile(np.array([[0., 1., 0.]]), (4, 1))))
+
+    # transform view frustum from (I, 0) to (R, t)
+    C2W = np.linalg.inv(W2C)
+    frustum_points = np.dot(np.hstack((frustum_points, np.ones_like(frustum_points[:, 0:1]))), C2W.T)
+    frustum_points = frustum_points[:, :3] / frustum_points[:, 3:4]
+
+    return frustum_points, frustum_lines, frustum_colors
+
+
+def frustums2lineset(frustums):
+    N = len(frustums)
+    merged_points = np.zeros((N*5, 3))      # 5 vertices per frustum
+    merged_lines = np.zeros((N*8, 2))       # 8 lines per frustum
+    merged_colors = np.zeros((N*8, 3))      # each line gets a color
+
+    for i, (frustum_points, frustum_lines, frustum_colors) in enumerate(frustums):
+        merged_points[i*5:(i+1)*5, :] = frustum_points
+        merged_lines[i*8:(i+1)*8, :] = frustum_lines + i*5
+        merged_colors[i*8:(i+1)*8, :] = frustum_colors
+
+    lineset = o3d.geometry.LineSet()
+    lineset.points = o3d.utility.Vector3dVector(merged_points)
+    lineset.lines = o3d.utility.Vector2iVector(merged_lines)
+    lineset.colors = o3d.utility.Vector3dVector(merged_colors)
+
+    return lineset
+
+def visualize_cameras(colored_camera_dicts, sphere_radius, camera_size=0.1, geometry_file=None, geometry_type='mesh'):
+    sphere = o3d.geometry.TriangleMesh.create_sphere(radius=sphere_radius, resolution=10)
+    sphere = o3d.geometry.LineSet.create_from_triangle_mesh(sphere)
+    sphere.paint_uniform_color((1, 0, 0))
+
+    coord_frame = o3d.geometry.TriangleMesh.create_coordinate_frame(size=0.5, origin=[0., 0., 0.])
+    things_to_draw = [sphere, coord_frame]
+
+    idx = 0
+    for color, camera_dict in colored_camera_dicts:
+        idx += 1
+
+        cnt = 0
+        frustums = []
+        for img_name in sorted(camera_dict.keys()):
+            K = np.array(camera_dict[img_name]['K']).reshape((4, 4))
+            W2C = np.array(camera_dict[img_name]['W2C']).reshape((4, 4))
+            C2W = np.linalg.inv(W2C)
+            img_size = camera_dict[img_name]['img_size']
+            frustums.append(get_camera_frustum(img_size, K, W2C, frustum_length=camera_size, color=color))
+            cnt += 1
+        cameras = frustums2lineset(frustums)
+        things_to_draw.append(cameras)
+
+    if geometry_file is not None:
+        if geometry_type == 'mesh':
+            geometry = o3d.io.read_triangle_mesh(geometry_file)
+            geometry.compute_vertex_normals()
+        elif geometry_type == 'pointcloud':
+            geometry = o3d.io.read_point_cloud(geometry_file)
+        else:
+            raise Exception('Unknown geometry_type: ', geometry_type)
+
+        things_to_draw.append(geometry)
+
+    o3d.visualization.draw_geometries(things_to_draw)
 
 def parse_matrix(matrix_str):
     rows = matrix_str.strip().split('] [')
@@ -121,8 +204,8 @@ def get_cam_points_vis(W, H, intrinsics, ext_pose, color,frustum_length):
         cam_points = np.concatenate((cam_points, np.linspace(cam[0][item[0]], cam[0][item[1]], num=1000, endpoint=True, retstep=False, dtype=None)))
     cam_points[:,0]*=-1
     cam_points = trimesh.points.PointCloud(vertices = cam_points, colors=[0, 255, 0, 255])
-    cam_points_vis = open3d.geometry.PointCloud()
-    cam_points_vis.points = open3d.utility.Vector3dVector(cam_points)
+    cam_points_vis = o3d.geometry.PointCloud()
+    cam_points_vis.points = o3d.utility.Vector3dVector(cam_points)
     cam_points_vis.paint_uniform_color(color)
     return cam_points_vis
 

vis_trajectory.py

@@ -0,0 +1,120 @@
+import trimesh
+import numpy as np
+import imageio
+import copy
+import cv2
+import os
+from glob import glob
+import open3d
+from multiprocessing import Pool
+import json
+from utils import *
+
+if __name__ == '__main__' :
+
+    H = 480
+    W = 720
+    intrinsics = np.array([[1000.,0.],
+                           [0., 1000.]])
+    
+    cam_path = "traj_vis/Hemi12_transforms.json"
+    location_path = "traj_vis/location_data_desert.json"
+    video_name = "D_loc1_61_t3n13_003d_Hemi12_1.json"
+
+    with open(location_path, 'r') as f: locations = json.load(f)
+    locations_info = {locations[idx]['name']:locations[idx] for idx in range(len(locations))}
+    location_name = video_name.split('_')[1]
+    location_info = locations_info[location_name]
+    translation = location_info['coordinates']['CameraTarget']['position']
+    vis_all = []
+    
+    # vis cam
+    with open(cam_path, 'r') as file:
+        data = json.load(file)
+    cam_poses = []
+    for i, key in enumerate(data.keys()):
+        if "C_" in key:
+            cam_poses.append(parse_matrix(data[key]))
+    cam_poses = np.stack(cam_poses)
+    cam_poses = np.transpose(cam_poses, (0,2,1))
+    cam_poses[:,:3,3] /= 100.
+    relative_pose = np.linalg.inv(cam_poses[0])
+    cam_num = len(cam_poses)
+    for idx in range(cam_num):
+        cam_pose = cam_poses[idx]
+        cam_pose = cam_pose[:, [1,2,0,3]]
+        cam_pose = relative_pose @ cam_pose
+        cam_points_vis = get_cam_points_vis(W, H, intrinsics, cam_pose, [0.4, 0.4, 0.4], frustum_length=1.)
+        vis_all.append(cam_points_vis)
+
+    # vis gt obj poses
+    start_frame_ind = 10
+    sample_n_frames = 77
+    frame_indices = np.linspace(start_frame_ind, start_frame_ind + sample_n_frames - 1, sample_n_frames, dtype=int)
+    
+    with open('traj_vis/'+video_name, 'r') as file:
+        data = json.load(file)
+    obj_poses = []
+    for i, key in enumerate(data.keys()):
+        obj_poses.append(parse_matrix(data[key][0]['matrix']))
+    obj_poses = np.stack(obj_poses)
+    obj_poses = np.transpose(obj_poses, (0,2,1))
+
+    obj_poses[:,:3,3] -= translation
+    obj_poses[:,:3,3] /= 100.
+    obj_poses = obj_poses[:, :, [1,2,0,3]]
+    obj_poses = relative_pose @ obj_poses
+    obj_poses = obj_poses[frame_indices]
+
+    obj_num = len(obj_poses)
+    for idx in range(obj_num):
+        obj_pose = obj_poses[idx]
+        if idx % 5 == 0:
+            cam_points_vis = get_cam_points_vis(W, H, intrinsics, obj_pose, [0.8, 0., 0.], frustum_length=0.5)
+            vis_all.append(cam_points_vis)
+
+    if len(data[key])>=2:
+        with open('traj_vis/'+video_name, 'r') as file:
+            data = json.load(file)
+        obj_poses = []
+        for i, key in enumerate(data.keys()):
+            obj_poses.append(parse_matrix(data[key][1]['matrix']))
+        obj_poses = np.stack(obj_poses)
+        obj_poses = np.transpose(obj_poses, (0,2,1))
+        obj_poses[:,:3,3] -= translation
+        obj_poses[:,:3,3] /= 100.
+        obj_poses = obj_poses[:, :, [1,2,0,3]]
+        obj_poses = relative_pose @ obj_poses
+        obj_poses = obj_poses[frame_indices]
+        obj_num = len(obj_poses)
+        for idx in range(obj_num):
+            obj_pose = obj_poses[idx]
+            if (idx % 5 == 0) :
+                cam_points_vis = get_cam_points_vis(W, H, intrinsics, obj_pose, [0., 0.8,0.], frustum_length=0.5)
+                vis_all.append(cam_points_vis)
+        
+    if len(data[key])>=3:
+        with open('traj_vis/'+video_name, 'r') as file:
+            data = json.load(file)
+        obj_poses = []
+        for i, key in enumerate(data.keys()):
+            obj_poses.append(parse_matrix(data[key][2]['matrix']))
+        obj_poses = np.stack(obj_poses)
+        obj_poses = np.transpose(obj_poses, (0,2,1))
+        obj_poses[:,:3,3] -= translation
+        obj_poses[:,:3,3] /= 100.
+        obj_poses = obj_poses[:, :, [1,2,0,3]]
+        obj_poses = relative_pose @ obj_poses
+        obj_poses = obj_poses[frame_indices]
+        obj_num = len(obj_poses)
+        for idx in range(obj_num):
+            obj_pose = obj_poses[idx]
+            if (idx % 5 == 0):
+                cam_points_vis = get_cam_points_vis(W, H, intrinsics, obj_pose, [0., 0., 0.8], frustum_length=0.5)
+                vis_all.append(cam_points_vis)
+
+    # vis coordinates
+    axis = open3d.geometry.TriangleMesh.create_coordinate_frame(size=2, origin=[0,0,0])
+    # vis_all.append(axis)
+    
+    open3d.visualization.draw_geometries(vis_all)