{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"ename": "ModuleNotFoundError",
"evalue": "No module named 'trimesh'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[1], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mnp\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mtrimesh\u001b[39;00m\n\u001b[1;32m 3\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mos\u001b[39;00m\n\u001b[1;32m 4\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mshutil\u001b[39;00m\n",
"\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'trimesh'"
]
}
],
"source": [
"import numpy as np\n",
"import trimesh\n",
"import os\n",
"import shutil\n",
"import imageio.v3 as imageio\n",
"from tqdm import tqdm"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"\n",
"def rotation_matrix(axis, angle):\n",
" \"\"\"\n",
" Returns a rotation matrix for a given axis and angle in radians.\n",
" :param axis: str, the axis to rotate around ('x', 'y', or 'z')\n",
" :param angle: float, the rotation angle in radians\n",
" :return: 3x3 rotation matrix\n",
" \"\"\"\n",
" if axis == 'x':\n",
" return np.array([[1, 0, 0],\n",
" [0, np.cos(angle), -np.sin(angle)],\n",
" [0, np.sin(angle), np.cos(angle)]])\n",
" elif axis == 'y':\n",
" return np.array([[np.cos(angle), 0, np.sin(angle)],\n",
" [0, 1, 0],\n",
" [-np.sin(angle), 0, np.cos(angle)]])\n",
" elif axis == 'z':\n",
" return np.array([[np.cos(angle), -np.sin(angle), 0],\n",
" [np.sin(angle), np.cos(angle), 0],\n",
" [0, 0, 1]])\n",
" else:\n",
" raise ValueError(\"Axis must be 'x', 'y', or 'z'.\")\n",
"\n",
"def rotate_point_cloud(point_cloud, rotations):\n",
" \"\"\"\n",
" Rotates a point cloud along specified axes by the given angles.\n",
" :param point_cloud: Nx3 numpy array of points\n",
" :param rotations: list of tuples [(axis, angle_in_degrees), ...]\n",
" Example: [('x', 90), ('y', 45)] for composite rotations\n",
" :return: Rotated point cloud as Nx3 numpy array\n",
" \"\"\"\n",
" rotated_cloud = point_cloud.copy()\n",
" for axis, angle in rotations:\n",
" angle_rad = np.radians(angle) # Convert degrees to radians\n",
" R = rotation_matrix(axis, angle_rad)\n",
" rotated_cloud = np.dot(rotated_cloud, R.T) # Apply rotation matrix\n",
" \n",
" return rotated_cloud\n"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[ 7.07106781e-01 0.00000000e+00 -7.07106781e-01]\n",
" [ 7.07106781e-01 6.12323400e-17 7.07106781e-01]\n",
" [ 4.32978028e-17 -1.00000000e+00 4.32978028e-17]]\n"
]
}
],
"source": [
"# Example point cloud (Nx3 matrix)\n",
"point_cloud = np.array([[1, 0, 0],\n",
" [0, 1, 0],\n",
" [0, 0, 1]])\n",
"\n",
"# Composite rotation: 90 degrees around x, then 45 degrees around y\n",
"rotations = [('x', 90), ('y', 45)]\n",
"\n",
"# Rotate the point cloud\n",
"rotated_cloud = rotate_point_cloud(point_cloud, rotations)\n",
"print(rotated_cloud)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": []
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"# rotate different to align in gso canonical space\n",
"# import open3d as o3d\n",
"# import numpy as np\n",
"import plotly.graph_objects as go\n",
"import matplotlib.pyplot as plt\n",
"import point_cloud_utils as pcu\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"def vis_colored_pcd(points, colors, size=1.0):\n",
"\n",
" fig = go.Figure(\n",
" data=[\n",
" go.Scatter3d(\n",
" x=points[:,0], y=points[:,1], z=points[:,2],\n",
" mode='markers',\n",
" marker=dict(size=size, color=colors)\n",
" )\n",
"\n",
" ],\n",
" layout=dict( \n",
" paper_bgcolor='rgba(0,0,0,0)', \n",
" width=512, \n",
" height=512,\n",
" scene=dict(\n",
" xaxis=dict(visible=False),\n",
" yaxis=dict(visible=False),\n",
" zaxis=dict(visible=False)\n",
" )\n",
" )\n",
" )\n",
" config = {\n",
" 'toImageButtonOptions': {\n",
" 'format': 'png', # one of png, svg, jpeg, webp\n",
" 'filename': 'custom_image',\n",
" 'height': 512,\n",
" 'width': 512,\n",
" 'scale':4 # Multiply title/legend/axis/canvas sizes by this factor\n",
" }\n",
"}\n",
"\n",
"\n",
" fig.show(config=config)\n",
"# fig.write_image(\"fig1.png\")\n",
"\n",
"# vis_colored_pcd(points, colors, size=1.3)\n",
"# vis_colored_pcd(split_points, splint_colors)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 84,
"metadata": {},
"outputs": [],
"source": [
"from functools import partial\n",
"# transformation dictionary\n",
"transformation_dict = {\n",
" 'gso': partial(rotate_point_cloud, rotations=[('x', 0)]), # no transformation\n",
" 'LGM': partial(rotate_point_cloud, rotations=[('x', 90)]),\n",
" 'CRM': partial(rotate_point_cloud, rotations=[('x', 90), ('z', 180)]),\n",
" 'Lara': partial(rotate_point_cloud, rotations=[('x', -110), ('z', 33)]),\n",
" 'ln3diff': partial(rotate_point_cloud, rotations=[('x', 90)]),\n",
" 'One-2-3-45': partial(rotate_point_cloud, rotations=[('x', 90), ('z', 180)]),\n",
" 'splatter-img': partial(rotate_point_cloud, rotations=[('x', -60)]),\n",
" # \n",
" 'OpenLRM': partial(rotate_point_cloud, rotations=[('x', 0)]),\n",
" 'shape-e': partial(rotate_point_cloud, rotations=[('x', 0)]),\n",
" 'GA/stage-2/dino_img/ditl-fromditlPCD-fixPose-tomesh-ditxlPCD': partial(rotate_point_cloud, rotations=[('x', 0)]),\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": 68,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"\n",
"# instance_name = '3D_Dollhouse_Happy_Brother_pcd_4096'\n",
"# instance_name = 'FRUIT_VEGGIE_DOMINO_GRADIENT_pcd_4096'\n",
"# instance_name = 'SpiderMan_Titan_Hero_12Inch_Action_Figure_5Hnn4mtkFsP_pcd_4096'\n",
"instance_name = 'Android_Figure_Panda_pcd_4096'\n",
"\n",
"method_name='LGM'\n",
"save_root=f\"/mnt/sfs-common/yslan/Repo/3dgen/FID-KID-Outputdir/3D-metrics-fps\"\n",
"\n",
"def vis_pcd(method_name, instance_name):\n",
"\n",
" pcd_path = os.path.join(save_root, method_name, f'{instance_name}.ply')\n",
" pcd = trimesh.load(pcd_path).vertices\n",
"\n",
" pcd = transformation_dict[method_name](pcd)\n",
"\n",
" color = np.zeros_like(pcd) # just black\n",
" vis_colored_pcd(pcd, color)\n",
"\n",
" # return pcd"
]
},
{
"cell_type": "code",
"execution_count": 85,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly",
"toImageButtonOptions": {
"filename": "custom_image",
"format": "png",
"height": 512,
"scale": 4,
"width": 512
}
},
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"source": [
"# vis_pcd('LGM', instance_name)\n",
"# vis_pcd('Lara', instance_name) # wrong\n",
"# vis_pcd('ln3diff', instance_name) # \n",
"# vis_pcd('CRM', instance_name) # \n",
"# vis_pcd('One-2-3-45', instance_name) # \n",
"# vis_pcd('splatter-img', instance_name) # \n",
"# vis_pcd('shape-e', instance_name) # \n",
"# vis_pcd('CRM', instance_name) # \n",
"# vis_pcd('OpenLRM', instance_name) # \n",
"\n",
"vis_pcd('GA/stage-2/dino_img/ditl-fromditlPCD-fixPose-tomesh-ditxlPCD', instance_name) # "
]
},
{
"cell_type": "code",
"execution_count": 87,
"metadata": {},
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},
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""
]
},
"metadata": {},
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}
],
"source": [
"vis_pcd('gso', instance_name)\n",
"# vis_pcd('shape-e', instance_name) # \n",
"# vis_pcd('LGM', instance_name) # \n",
"# vis_pcd('splatter-img', instance_name) # "
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"# organize a dataset for fid eval\n",
"\n",
"objv_dataset = '/mnt/sfs-common/yslan/Dataset/Obajverse/chunk-jpeg-normal/bs_16_fixsave3/170K/512/'\n",
"dataset_json = os.path.join(objv_dataset, 'dataset.json')"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"with open(dataset_json, 'r') as f:\n",
" dataset_json = json.load(f)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"dict_keys(['Transportations_tar', 'Furnitures', 'Food', 'BuildingsOutdoor', 'Electronics', 'daily-used', 'Human-Shape', 'Plants', 'Animals'])"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataset_json.keys()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"37461"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(dataset_json['Animals'])"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"# instances_for_use = dataset_json['Animals'][::3][:6250]\n",
"instances_for_use = dataset_json['Animals'][::3][:6250][1100:2200]\n",
"# instances_for_use = dataset_json['Animals'][:6250]"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['Animals/53/275475/1', 'Animals/53/278344/1', 'Animals/53/279428/1']"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# len(instances_for_use)\n",
"instances_for_use[:3]"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|██████████| 1100/1100 [01:32<00:00, 11.87it/s]\n"
]
}
],
"source": [
"\n",
"# save to local dir, with the same format as obj_folder, 8 images \n",
"# output_dir = '/mnt/sfs-common/yslan/Dataset/Obajverse/Objv-animals-for-FID_eval'\n",
"output_dir = '/mnt/sfs-common/yslan/Dataset/Obajverse/Objv-animals-for-FID_eval-new'\n",
"# output_dir = '/mnt/sfs-common/yslan/Dataset/Obajverse/Objv-animals-for-FID_eval-2K'\n",
"# output_dir = '/mnt/sfs-common/yslan/Dataset/Obajverse/Objv-animals-for-FID_eval-2K-new'\n",
"\n",
"# for object in instances_for_use:\n",
"for idx, object in enumerate(tqdm(instances_for_use[:])):\n",
" img_path = os.path.join(objv_dataset, object, 'raw_img.jpg')\n",
" img = imageio.imread(img_path)\n",
"\n",
" if idx % 3 == 0:\n",
" indices_to_save = [0,1]\n",
" else:\n",
" indices_to_save = [1,0]\n",
" # indices_to_save = [0,1,2,3,4,9,10,11,12][:2]\n",
" # else:\n",
" # indices_to_save = [1,2,3,4,9,10,11,12]\n",
"\n",
" instance_output_dir = os.path.join(output_dir, object)\n",
" os.makedirs(instance_output_dir, exist_ok=True)\n",
"\n",
" for idx, w_position in enumerate(indices_to_save):\n",
" patch = img[:, w_position*512:(w_position+1)*512, :]\n",
" imageio.imwrite(os.path.join(instance_output_dir, f'{idx}.jpg'), patch)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"# convert gt pcd to the right format\n",
"\n",
"\n",
"\n",
"objv_dataset = '/mnt/sfs-common/yslan/Dataset/Obajverse/chunk-jpeg-normal/bs_16_fixsave3/170K/512/'\n",
"dataset_json = os.path.join(objv_dataset, 'dataset.json')\n",
"with open(dataset_json, 'r') as f:\n",
" dataset_json = json.load(f)\n",
"\n",
"all_objs = dataset_json['Animals'][::3][1100:2200]"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|██████████| 1100/1100 [00:33<00:00, 32.89it/s]\n"
]
}
],
"source": [
"# from tqdm import tqdm \n",
"# import shutil\n",
"\n",
"# ! copy gt\n",
"\n",
"gt_path = \"/mnt/sfs-common/yslan/Dataset/Obajverse/FPS_PCD/pcd-V=10_4096_polish_fullset/fps-pcd\"\n",
"output_path = \"/mnt/sfs-common/yslan/Repo/3dgen/FID-KID-Outputdir-objv/3D-metrics-fps/objv-gt\"\n",
"\n",
"for obj_folder in tqdm(all_objs):\n",
" save_name = '-'.join(obj_folder.split('/'))\n",
" obj_folder = '/'.join(obj_folder.split('/')[:-1])\n",
"\n",
" shutil.copy(os.path.join(gt_path, obj_folder, 'fps-4096.ply'), os.path.join(output_path, f'{save_name}_pcd_4096.ply'))"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|██████████| 1100/1100 [00:14<00:00, 77.74it/s]\n"
]
}
],
"source": [
"# ! copy ours pred\n",
"\n",
"pred_path = \"/mnt/sfs-common/yslan/Repo/3dgen/FID-KID-Outputdir-objv/GA/stage-2/dino_img/ditl-fromditlPCD\"\n",
"output_path = \"/mnt/sfs-common/yslan/Repo/3dgen/FID-KID-Outputdir-objv/3D-metrics-fps/GA\"\n",
"\n",
"for obj_folder in tqdm(all_objs[:]):\n",
" save_name = '-'.join(obj_folder.split('/'))\n",
" obj_folder = '/'.join(obj_folder.split('/')[1:-1])\n",
" try:\n",
" shutil.copy(os.path.join(pred_path, obj_folder, '0', 'sample-0-gaussian-4096.ply'), os.path.join(output_path, f'{save_name}_pcd_4096.ply'))\n",
" except:\n",
" continue"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"# copy output images into a single folder for clean-FID calculation\n",
"\n",
"\n",
"objv_dataset = '/mnt/sfs-common/yslan/Dataset/Obajverse/chunk-jpeg-normal/bs_16_fixsave3/170K/512/'\n",
"dataset_json = os.path.join(objv_dataset, 'dataset.json')\n",
"with open(dataset_json, 'r') as f:\n",
" dataset_json = json.load(f)\n",
"\n",
"# all_objs = dataset_json['Animals'][::3][:6250]\n",
"all_objs = dataset_json['Animals'][::3][1100:2200]\n",
"all_objs = all_objs[:600]\n"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|██████████| 600/600 [00:00<00:00, 17405.80it/s]\n",
"100%|██████████| 14400/14400 [03:20<00:00, 71.66it/s]\n"
]
}
],
"source": [
"\n",
"import shutil\n",
"\n",
"# for method_name in ln3diff-fixpose_192 CRM \n",
"# for method_name in \n",
"# OpenLRM/Animals One-2-3-45/Animals shape-e/Animals splatter-img/Animals \n",
"\n",
"output_path='/mnt/sfs-common/yslan/Repo/3dgen/FID-KID-Outputdir-objv'\n",
"\n",
"# for method_name in ['LGM_fixpose', 'GA-fixpose']:\n",
"# for method_name in []:\n",
"# for method_name in ['LGM_fixpose/Animals', 'GA/stage-2/dino_img/ditl-fromditlPCD/']:\n",
"for method_name in ['GA/stage-2/dino_img/ditl-fromditlPCD/']:\n",
"# for method_name in ['objv-gt']:\n",
" path = os.path.join(output_path, method_name)\n",
" files = []\n",
"\n",
" for obj_folder in tqdm(all_objs):\n",
" obj_folder = '/'.join(obj_folder.split('/')[1:])\n",
" for idx in range(24):\n",
" # files.append(os.path.join(path, obj_folder, f'{idx}.jpg'))\n",
" if 'Lara' in path:\n",
" files.append(os.path.join(path, '/'.join(obj_folder.split('/')[:-1]), '0.jpg', f'{idx}.jpg'))\n",
" # elif 'LGM' in path:\n",
" # files.append(os.path.join(path, '/'.join(obj_folder.split('/')[:-1]), '0', f'{idx}.jpg'))\n",
" elif 'GA' in path:\n",
" files.append(os.path.join(path, '/'.join(obj_folder.split('/')[:-1]), '0', f'sample-0-{idx}.jpg'))\n",
" elif 'LRM' in path:\n",
" files.append(os.path.join(path, '/'.join(obj_folder.split('/')[:-1]), '0', f'{idx}.jpg'))\n",
" else:\n",
" files.append(os.path.join(path, obj_folder, '0', f'{idx}.jpg'))\n",
"\n",
"\n",
"\n",
" output_path = '/mnt/sfs-common/yslan/Repo/3dgen/FID-KID-Outputdir-objv/lint-dir'\n",
"\n",
" method_output_path = os.path.join(output_path, method_name)\n",
" os.makedirs(method_output_path, exist_ok=True)\n",
"\n",
" for idx, file_path in enumerate(tqdm(files[:])):\n",
" shutil.copy(file_path, os.path.join(method_output_path, f'{idx}.jpg'))\n"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|██████████| 10/10 [00:00<00:00, 60.38it/s]\n"
]
}
],
"source": []
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'/mnt/sfs-common/yslan/Dataset/Obajverse/Objv-animals-for-FID_eval-new/LGM_fixpose/Animals/9.jpg'"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"os.path.join(method_output_path, f'{idx}.jpg')"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|██████████| 600/600 [00:00<00:00, 20171.71it/s]\n"
]
}
],
"source": [
"gso_rendering=\"/mnt/sfs-common/yslan/Dataset/Obajverse/Objv-animals-for-FID_eval-2K\"\n",
"\n",
"\n",
"# for method_name in ['GA/stage-2/dino_img/ditl-fromditlPCD/']:\n",
"# # for method_name in ['objv-gt']:\n",
"# path = os.path.join(output_path, method_name)\n",
"files = []\n",
"\n",
"for obj_folder in tqdm(all_objs):\n",
" obj_folder = obj_folder[:-2] # to load 3 chunks\n",
" for batch in range(1,4):\n",
" for idx in range(8):\n",
" files.append(os.path.join(gso_rendering, obj_folder, str(batch), f'{idx}.jpg'))\n"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|██████████| 14400/14400 [04:21<00:00, 55.06it/s]\n"
]
}
],
"source": [
"\n",
"output_path = '/mnt/sfs-common/yslan/Repo/3dgen/FID-KID-Outputdir-objv/lint-dir'\n",
"gt_output_path = os.path.join(output_path, 'objv-gt')\n",
"\n",
"os.makedirs(gt_output_path, exist_ok=True)\n",
"\n",
"for idx, file_path in enumerate(tqdm(files[:])):\n",
" shutil.copy(file_path, os.path.join(gt_output_path, f'{idx}.jpg'))"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"all_vid_paths = \"/mnt/sfs-common/yslan/Repo/3dgen/FID-KID-Outputdir-free3d/GA-fixpose/2-30_CONSTRUCTION_SET-0-sample-0-gs.mp4 /mnt/sfs-common/yslan/Repo/3dgen/FID-KID-Outputdir-free3d/GA-fixpose/60-BAGEL_WITH_CHEESE-0-sample-0-gs.mp4 /mnt/sfs-common/yslan/Repo/3dgen/FID-KID-Outputdir-free3d/GA-fixpose/62-BALANCING_CACTUS-0-sample-0-gs.mp4 /mnt/sfs-common/yslan/Repo/3dgen/FID-KID-Outputdir-free3d/GA-fixpose/76-Baby_Elements_Stacking_Cups-0-sample-0-gs.mp4 /mnt/sfs-common/yslan/Repo/3dgen/FID-KID-Outputdir-free3d/GA-fixpose/98-Breyer_Horse_Of_The_Year_2015-0-sample-0-gs.mp4 /mnt/sfs-common/yslan/Repo/3dgen/FID-KID-Outputdir-free3d/GA-fixpose/112-COAST_GUARD_BOAT-0-sample-0-gs.mp4 /mnt/sfs-common/yslan/Repo/3dgen/FID-KID-Outputdir-free3d/GA-fixpose/113-CONE_SORTING-0-sample-0-gs.mp4 /mnt/sfs-common/yslan/Repo/3dgen/FID-KID-Outputdir-free3d/GA-fixpose/115-CREATIVE_BLOCKS_35_MM-0-sample-0-gs.mp4 /mnt/sfs-common/yslan/Repo/3dgen/FID-KID-Outputdir-free3d/GA-fixpose/155-Cole_Hardware_Mini_Honey_Dipper-0-sample-0-gs.mp4 /mnt/sfs-common/yslan/Repo/3dgen/FID-KID-Outputdir-free3d/GA-fixpose/275-FAIRY_TALE_BLOCKS-0-sample-0-gs.mp4 /mnt/sfs-common/yslan/Repo/3dgen/FID-KID-Outputdir-free3d/GA-fixpose/277-FIRE_ENGINE-0-sample-0-gs.mp4 /mnt/sfs-common/yslan/Repo/3dgen/FID-KID-Outputdir-free3d/GA-fixpose/280-FOOD_BEVERAGE_SET-0-sample-0-gs.mp4 /mnt/sfs-common/yslan/Repo/3dgen/FID-KID-Outputdir-free3d/GA-fixpose/303-GEOMETRIC_PEG_BOARD-0-sample-0-gs.mp4 /mnt/sfs-common/yslan/Repo/3dgen/FID-KID-Outputdir-free3d/GA-fixpose/324-Great_Dinos_Triceratops_Toy-0-sample-0-gs.mp4 /mnt/sfs-common/yslan/Repo/3dgen/FID-KID-Outputdir-free3d/GA-fixpose/365-JUICER_SET-0-sample-0-gs.mp4 /mnt/sfs-common/yslan/Repo/3dgen/FID-KID-Outputdir-free3d/GA-fixpose/789-STACKING_BEAR-0-sample-0-gs.mp4 /mnt/sfs-common/yslan/Repo/3dgen/FID-KID-Outputdir-free3d/GA-fixpose/791-STACKING_RING-0-sample-0-gs.mp4 /mnt/sfs-common/yslan/Repo/3dgen/FID-KID-Outputdir-free3d/GA-fixpose/803-Schleich_African_Black_Rhino-0-sample-0-gs.mp4 \""
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['BAGEL_WITH_CHEESE',\n",
" 'BALANCING_CACTUS',\n",
" 'Baby_Elements_Stacking_Cups',\n",
" 'Breyer_Horse_Of_The_Year_2015',\n",
" 'COAST_GUARD_BOAT',\n",
" 'CONE_SORTING',\n",
" 'CREATIVE_BLOCKS_35_MM',\n",
" 'Cole_Hardware_Mini_Honey_Dipper',\n",
" 'FAIRY_TALE_BLOCKS',\n",
" 'FIRE_ENGINE',\n",
" 'FOOD_BEVERAGE_SET',\n",
" 'GEOMETRIC_PEG_BOARD',\n",
" 'Great_Dinos_Triceratops_Toy',\n",
" 'JUICER_SET',\n",
" 'STACKING_BEAR',\n",
" 'STACKING_RING',\n",
" 'Schleich_African_Black_Rhino']"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"instances = [\n",
" path.split('/')[-1].split('-')[1]\n",
" for path in all_vid_paths.split()\n",
"]\n",
"instances[1:]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "base",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.5"
}
},
"nbformat": 4,
"nbformat_minor": 2
}