1057 lines
42 KiB
Plaintext
1057 lines
42 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 12,
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||
"id": "805fb727",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"import pandas as pd\n",
|
||
"import numpy as np\n",
|
||
"import cv2 as cv\n",
|
||
"from scipy.spatial.transform import Rotation as R"
|
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]
|
||
},
|
||
{
|
||
"cell_type": "code",
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"execution_count": 13,
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"id": "456ca3a7",
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"metadata": {},
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"outputs": [],
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"source": [
|
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"path = \"/home/ivan/ivan/git/work_drivecast2/SLAM/ORB_SLAM3-1.0-release/Examples/Stereo/CameraTrajectory.txt\"\n",
|
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"traj = pd.read_csv(path, sep=\" \")"
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]
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},
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{
|
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"cell_type": "code",
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"execution_count": 14,
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"id": "95b5c6ad",
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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|
||
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|
||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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|
||
" <td>0.323237</td>\n",
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||
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||
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||
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||
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||
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||
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||
" <td>0.999747</td>\n",
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||
" <td>0.017154</td>\n",
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||
" <td>0.014546</td>\n",
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||
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||
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||
" <td>0.999853</td>\n",
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||
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||
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||
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||
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||
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||
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||
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||
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||
" <td>0.999805</td>\n",
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||
" <td>0.015107</td>\n",
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||
" <td>0.012714</td>\n",
|
||
" <td>0.345279</td>\n",
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||
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||
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||
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||
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||
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||
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||
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" <td>0.999848</td>\n",
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||
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||
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"</table>\n",
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"text/plain": [
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"... ... ... ... ... ... \n",
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"... ... ... \n",
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"1095 0.999842 298.364136 \n",
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"[1100 rows x 12 columns]"
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]
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},
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"execution_count": 14,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"traj"
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]
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},
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{
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"cell_type": "code",
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||
"execution_count": 15,
|
||
"id": "77d852aa",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"with open(\"/home/ivan/Downloads/Telegram Desktop/test_data.json\") as f:\n",
|
||
" traj_example = json.load(f)"
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||
]
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||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 16,
|
||
"id": "2eb4a8c7",
|
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"metadata": {},
|
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"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{'frame': 2,\n",
|
||
" 'poses': [{'camera_id': 0,\n",
|
||
" 'Euler angles': [179.0592276314431, 178.71021095455262, 12.371121058785771],\n",
|
||
" 'xyz coords': [1598.4821251839471, 294.28354659765137, -65.4766852385318]},\n",
|
||
" {'object_id': 2,\n",
|
||
" 'Euler angles': [179.0592276314431, 178.71021095455262, 12.371121058785771],\n",
|
||
" 'xyz coords': [1598.4821251839471, 294.28354659765137, -65.4766852385318]}]}"
|
||
]
|
||
},
|
||
"execution_count": 16,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"traj_example[\"data\"][1]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 24,
|
||
"id": "b30e79c9",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"json_traj_example = {\"data\": [\n",
|
||
" {\"frame\":0, \n",
|
||
" \"poses\":{\n",
|
||
" \"euler_angles\":[0.0,0.0,0.0],\n",
|
||
" \"xyz_coords\":[0.0,0.0,0.0]\n",
|
||
" }\n",
|
||
" }\n",
|
||
" ]\n",
|
||
" }\n",
|
||
"\n",
|
||
"json_traj = {\"data\": [\n",
|
||
" ]\n",
|
||
" }\n",
|
||
"\n",
|
||
"# Fill the first line\n",
|
||
"Twc = traj.loc[0]\n",
|
||
"# ---- Using SciPy ----\n",
|
||
"Rot = R.from_matrix([[Twc[0], Twc[1], Twc[2]], \n",
|
||
" [Twc[4], Twc[5], Twc[6]], \n",
|
||
" [Twc[8], Twc[9], Twc[10]]])\n",
|
||
"# \"zxy\" axes in which the data was written.\n",
|
||
"euler = Rot.as_euler('zxy', degrees=True)\n",
|
||
"\n",
|
||
"\n",
|
||
"# ---- Using OpenCV ----\n",
|
||
"# mat = np.array([[Twc[0], Twc[1], Twc[2]], \n",
|
||
"# [Twc[4], Twc[5], Twc[6]], \n",
|
||
"# [Twc[8], Twc[9], Twc[10]]])\n",
|
||
"# euler, _ = cv.Rodrigues(mat)\n",
|
||
"# print(euler)\n",
|
||
"\n",
|
||
"\n",
|
||
"# Coordinate system in ORB-SLAM3: ZXY. Coordinate system in UE4: XYZ \n",
|
||
"entry = {\"frame\":0, \"poses\":[{\"camera_id\":0, \"euler_angles\":[-euler[0], -euler[1], -euler[2]], \n",
|
||
" \"xyz_coords\":[-Twc[7], Twc[11], Twc[3]]},\n",
|
||
" {\"cube_id\":0, \"euler_angles\":[0.0, 0.0, 0.0], \n",
|
||
" \"xyz_coords\":[-33.81, 5.15, 0.82]},\n",
|
||
" {\"cube_id\":1, \"euler_angles\":[0.0, 0.0, 0.0], \n",
|
||
" \"xyz_coords\":[-11.5, 0.7, 0.56]},\n",
|
||
" {\"cube_id\":2, \"euler_angles\":[0.0, 0.0, 0.0], \n",
|
||
" \"xyz_coords\":[-95.0, 5.15, 0.8]},\n",
|
||
" {\"cube_id\":3, \"euler_angles\":[0.0, 0.0, 0.0], \n",
|
||
" \"xyz_coords\":[-130.3, 4.6, 2.1]},\n",
|
||
" {\"cube_id\":4, \"euler_angles\":[0.0, 0.0, 0.0], \n",
|
||
" \"xyz_coords\":[-346.5, 4.1, 5.9]},\n",
|
||
" {\"cube_id\":5, \"euler_angles\":[0.0, 0.0, 0.0], \n",
|
||
" \"xyz_coords\":[-346.5, 25.7, 4.8]},\n",
|
||
" ]\n",
|
||
" }\n",
|
||
"json_traj[\"data\"].append(entry)\n",
|
||
"\n",
|
||
"\n",
|
||
"for i in range(1, len(traj.index)):\n",
|
||
" Twc = traj.loc[i]\n",
|
||
" Rot = R.from_matrix([[Twc[0], Twc[1], Twc[2]], \n",
|
||
" [Twc[4], Twc[5], Twc[6]], \n",
|
||
" [Twc[8], Twc[9], Twc[10]]])\n",
|
||
" # \"zxy\" axes in which the data was written.\n",
|
||
" euler = Rot.as_euler('zxy', degrees=True)\n",
|
||
" entry = {\"frame\":i, \"poses\":\n",
|
||
" [\n",
|
||
" {\"camera_id\":0, \"euler_angles\":[-euler[0], -euler[1], -euler[2]], \n",
|
||
" \"xyz_coords\":[Twc[7], Twc[11], Twc[3]]}\n",
|
||
" ]\n",
|
||
" }\n",
|
||
" json_traj[\"data\"].append(entry)"
|
||
]
|
||
},
|
||
{
|
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|
||
" {'frame': 399,\n",
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" 'xyz_coords': [-2.349857807, 193.513824463, -16.387588501]}]}]"
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]
|
||
},
|
||
"execution_count": 23,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
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||
}
|
||
],
|
||
"source": [
|
||
"json_traj[\"data\"][300:400]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 18,
|
||
"id": "ec96c736",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"with open('cameraTraj_UE4_format.json', 'w') as f:\n",
|
||
" json.dump(json_traj, f, indent=2)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "13093b0d",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": []
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "e9095c85",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": []
|
||
}
|
||
],
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||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "Python 3 (ipykernel)",
|
||
"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": "3.8.10"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 5
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||
}
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