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video_id
large_stringclasses
1 value
frame_index
int64
1
2.79k
timestamp
large_stringlengths
5
5
class_label
large_stringclasses
21 values
x_min
float64
0
3.75k
y_min
float64
0
2.02k
x_max
float64
72.3
3.84k
y_max
float64
103
2.16k
confidence_score
float64
0.35
0.99
detector_name
large_stringclasses
1 value
YcvECxtXoxQ
1
00:00
Front-wheel
1,948.369995
1,340.97876
2,605.91748
2,099.241943
0.952252
best.pt
YcvECxtXoxQ
1
00:00
Fender
1,806.858032
875.908081
2,650.978027
1,698.734375
0.951791
best.pt
YcvECxtXoxQ
1
00:00
Front-door
1,114.462402
507.500244
1,920.109863
1,713.42334
0.936848
best.pt
YcvECxtXoxQ
1
00:00
Front-wheel
269.197266
1,232.105957
767.036316
1,849.763184
0.857159
best.pt
YcvECxtXoxQ
1
00:00
Hood
0
724.571289
284.274292
849.231689
0.675201
best.pt
YcvECxtXoxQ
1
00:00
Rocker-panel
662.791626
1,627.357422
1,963.591919
1,838.145752
0.609315
best.pt
YcvECxtXoxQ
1
00:00
Back-door
486.486938
510.620178
1,212.689697
1,656.498779
0.5644
best.pt
YcvECxtXoxQ
1
00:00
Front-window
1,216.900879
556.801575
1,756.522949
898.78949
0.514489
best.pt
YcvECxtXoxQ
1
00:00
Hood
1,664.404541
549.094666
2,715.737549
946.752502
0.436784
best.pt
YcvECxtXoxQ
1
00:00
Fender
195.949493
586.614746
602.930786
1,087.510498
0.411047
best.pt
YcvECxtXoxQ
1
00:00
Fender
167.454575
588.888428
600.866577
1,496.704102
0.379994
best.pt
YcvECxtXoxQ
2
00:01
Front-wheel
1,947.24939
1,340.907593
2,606.500977
2,098.741699
0.969854
best.pt
YcvECxtXoxQ
2
00:01
Fender
1,807.62854
878.19342
2,656.157715
1,694.755127
0.963634
best.pt
YcvECxtXoxQ
2
00:01
Front-door
1,114.677612
507.244629
1,923.012085
1,711.077881
0.943959
best.pt
YcvECxtXoxQ
2
00:01
Front-wheel
267.903748
1,231.533569
767.604004
1,849.380615
0.869407
best.pt
YcvECxtXoxQ
2
00:01
Hood
0
724.525452
284.787506
848.487122
0.667527
best.pt
YcvECxtXoxQ
2
00:01
Rocker-panel
657.481506
1,628.128418
1,960.29126
1,835.508911
0.615351
best.pt
YcvECxtXoxQ
2
00:01
Back-door
490.542419
510.326294
1,215.420044
1,663.463623
0.577408
best.pt
YcvECxtXoxQ
2
00:01
Front-window
1,226.96814
557.45752
1,759.699707
899.026855
0.523581
best.pt
YcvECxtXoxQ
2
00:01
Front-bumper
2,475.133789
1,124.734741
3,742.318848
1,820.817627
0.511935
best.pt
YcvECxtXoxQ
2
00:01
Hood
1,669.641357
556.270203
2,727.321533
926.932617
0.464694
best.pt
YcvECxtXoxQ
2
00:01
Fender
195.192383
586.110718
602.693726
1,088.049561
0.43179
best.pt
YcvECxtXoxQ
2
00:01
Fender
167.565582
589.06134
601.249695
1,469.759033
0.422188
best.pt
YcvECxtXoxQ
3
00:02
Fender
1,808.076416
878.726074
2,657.133545
1,696.062378
0.966323
best.pt
YcvECxtXoxQ
3
00:02
Front-wheel
1,948.07959
1,341.554932
2,605.604004
2,100.209961
0.965796
best.pt
YcvECxtXoxQ
3
00:02
Front-door
1,115.101563
507.735168
1,923.121948
1,715.154419
0.942804
best.pt
YcvECxtXoxQ
3
00:02
Front-wheel
268.574829
1,231.829346
767.847717
1,848.549805
0.869999
best.pt
YcvECxtXoxQ
3
00:02
Hood
0
724.461548
283.568481
848.604858
0.683027
best.pt
YcvECxtXoxQ
3
00:02
Rocker-panel
657.131897
1,630.945313
1,964.278931
1,841.382568
0.640335
best.pt
YcvECxtXoxQ
3
00:02
Back-door
494.187744
513.49054
1,211.963745
1,656.960571
0.586175
best.pt
YcvECxtXoxQ
3
00:02
Front-window
1,226.1604
557.926208
1,757.858398
900.686462
0.518828
best.pt
YcvECxtXoxQ
3
00:02
Front-bumper
2,479.817383
1,120.518555
3,741.009766
1,817.337524
0.491653
best.pt
YcvECxtXoxQ
3
00:02
Hood
1,670.270996
549.545288
2,719.365723
924.80896
0.46232
best.pt
YcvECxtXoxQ
3
00:02
Fender
196.19696
586.570679
601.806335
1,087.796997
0.416291
best.pt
YcvECxtXoxQ
3
00:02
Fender
167.484009
588.839355
599.660767
1,517.644409
0.393398
best.pt
YcvECxtXoxQ
4
00:03
Front-wheel
1,948.634033
1,341.176025
2,605.217285
2,101.515137
0.954777
best.pt
YcvECxtXoxQ
4
00:03
Fender
1,809.112793
877.671387
2,655.189453
1,694.853149
0.95259
best.pt
YcvECxtXoxQ
4
00:03
Front-door
1,115.191162
507.440674
1,921.545654
1,710.821289
0.938945
best.pt
YcvECxtXoxQ
4
00:03
Front-wheel
268.368256
1,232.501465
768.889893
1,848.623535
0.855408
best.pt
YcvECxtXoxQ
4
00:03
Hood
0
724.681091
283.569305
848.214294
0.714193
best.pt
YcvECxtXoxQ
4
00:03
Rocker-panel
661.78186
1,629.150146
1,963.782471
1,841.049683
0.599617
best.pt
YcvECxtXoxQ
4
00:03
Back-door
485.792999
510.486511
1,214.919556
1,657.003052
0.569289
best.pt
YcvECxtXoxQ
4
00:03
Front-window
1,224.921387
556.398499
1,762.432251
900.981445
0.505774
best.pt
YcvECxtXoxQ
4
00:03
Fender
198.746796
586.505432
600.902466
1,086.213867
0.442665
best.pt
YcvECxtXoxQ
4
00:03
Fender
169.556305
589.488831
599.310547
1,431.869385
0.397556
best.pt
YcvECxtXoxQ
4
00:03
Front-bumper
2,472.251709
1,107.765625
3,738.432129
1,816.039551
0.355224
best.pt
YcvECxtXoxQ
5
00:04
Mirror
948.439453
518.427368
1,148.922119
693.899658
0.908522
best.pt
YcvECxtXoxQ
5
00:04
Front-window
1,119.123901
333.985474
1,281.19873
677.976196
0.830199
best.pt
YcvECxtXoxQ
5
00:04
Fender
1,049.128174
629.730469
1,354.289307
1,449.560547
0.809118
best.pt
YcvECxtXoxQ
5
00:04
Front-wheel
1,127.250488
1,096.814453
1,476.478027
1,937.321533
0.638404
best.pt
YcvECxtXoxQ
5
00:04
Grille
1,763.102051
978.002747
3,113.283691
1,323.713867
0.575478
best.pt
YcvECxtXoxQ
5
00:04
Mirror
951.171753
522.347046
1,161.026733
766.775513
0.540205
best.pt
YcvECxtXoxQ
5
00:04
Grille
1,847.147827
1,383.711182
3,147.345215
1,661.322876
0.480985
best.pt
YcvECxtXoxQ
5
00:04
Front-door
1,077.088623
325.361023
1,292.221802
1,353.53833
0.416153
best.pt
YcvECxtXoxQ
5
00:04
Front-door
978.73291
320.622986
1,279.088623
1,329.438721
0.380352
best.pt
YcvECxtXoxQ
6
00:05
Mirror
877.975525
525.897034
1,090.795898
724.773926
0.830963
best.pt
YcvECxtXoxQ
6
00:05
Front-door
860.784119
316.10675
1,173.309326
1,406.001343
0.810299
best.pt
YcvECxtXoxQ
6
00:05
Fender
1,031.172729
650.184937
1,417.452759
1,437.252808
0.783668
best.pt
YcvECxtXoxQ
6
00:05
Rocker-panel
822.053284
1,146.253784
1,072.199951
1,532.351318
0.527657
best.pt
YcvECxtXoxQ
6
00:05
Grille
1,866.053467
1,002.405212
3,167.666992
1,330.927734
0.462891
best.pt
YcvECxtXoxQ
6
00:05
Mirror
881.112854
524.297119
1,083.485352
671.647583
0.457313
best.pt
YcvECxtXoxQ
6
00:05
Mirror
2,584.029053
579.649658
2,719.636963
679.115295
0.451021
best.pt
YcvECxtXoxQ
6
00:05
Front-wheel
1,079.651123
1,105.235229
1,437.897461
1,948.109985
0.357747
best.pt
YcvECxtXoxQ
6
00:05
Grille
1,624.686768
1,354.505615
3,129.82959
1,691.386597
0.352449
best.pt
YcvECxtXoxQ
7
00:06
Front-door
770.775513
333.46637
1,192.876465
1,432.178467
0.773747
best.pt
YcvECxtXoxQ
7
00:06
Mirror
828.609009
525.317383
1,058.949829
765.89917
0.761855
best.pt
YcvECxtXoxQ
7
00:06
Back-wheel
638.473999
1,055.056885
870.993164
1,618.383911
0.680802
best.pt
YcvECxtXoxQ
7
00:06
Fender
988.920044
651.2276
1,453.780518
1,470.244995
0.658931
best.pt
YcvECxtXoxQ
7
00:06
Rocker-panel
728.463501
1,280.09436
1,065.191406
1,558.116211
0.595495
best.pt
YcvECxtXoxQ
7
00:06
Front-wheel
1,073.322266
1,101.483765
1,482.329834
1,955.262451
0.557912
best.pt
YcvECxtXoxQ
7
00:06
Grille
1,968.756226
999.970215
3,163.797363
1,327.075806
0.51544
best.pt
YcvECxtXoxQ
7
00:06
Hood
1,172.786865
320.325165
2,569.680176
753.279297
0.499908
best.pt
YcvECxtXoxQ
7
00:06
Fender
627.147217
648.945801
852.461243
1,373.849365
0.489444
best.pt
YcvECxtXoxQ
7
00:06
Back-wheel
1,067.206421
1,109.129639
1,477.498535
1,966.119385
0.422039
best.pt
YcvECxtXoxQ
7
00:06
Front-door
765.023071
483.338867
1,315.242676
1,449.745117
0.378478
best.pt
YcvECxtXoxQ
7
00:06
Mirror
831.813965
524.747803
1,046.914429
703.414185
0.356246
best.pt
YcvECxtXoxQ
8
00:07
Mirror
3,082.259033
746.391907
3,264.378662
908.709778
0.886719
best.pt
YcvECxtXoxQ
8
00:07
Tail-light
1,785.983276
582.302734
2,350.181641
846.100891
0.850299
best.pt
YcvECxtXoxQ
8
00:07
Back-wheel
2,234.314941
1,307.646484
2,796.168945
2,157.158447
0.830417
best.pt
YcvECxtXoxQ
8
00:07
Rocker-panel
2,793.791992
1,477.505493
3,227.410156
1,739.740356
0.796824
best.pt
YcvECxtXoxQ
8
00:07
Roof
1,735.036377
115.35022
2,583.748047
346.729156
0.611993
best.pt
YcvECxtXoxQ
8
00:07
Back-windshield
451.401917
187.827118
1,912.284668
831.359436
0.611447
best.pt
YcvECxtXoxQ
8
00:07
Fender
3,202.085449
1,087.812256
3,368.311523
1,489.457764
0.582826
best.pt
YcvECxtXoxQ
8
00:07
License-plate
574.265137
901.504395
1,143.374756
1,174.677002
0.500778
best.pt
YcvECxtXoxQ
8
00:07
Front-wheel
3,091.786377
1,153.873291
3,358.573975
1,753.259399
0.436015
best.pt
YcvECxtXoxQ
8
00:07
Back-window
2,302.57666
293.912292
2,544.629395
715.59082
0.384816
best.pt
YcvECxtXoxQ
9
00:08
Mirror
3,080.040527
717.682068
3,262.229004
870.673828
0.92305
best.pt
YcvECxtXoxQ
9
00:08
Tail-light
1,783.654907
523.977722
2,339.242188
793.719482
0.82883
best.pt
YcvECxtXoxQ
9
00:08
Front-wheel
3,085.325195
1,125.373291
3,351.895996
1,726.835938
0.777408
best.pt
YcvECxtXoxQ
9
00:08
Rocker-panel
2,785.453857
1,463.172119
3,221.119141
1,695.165039
0.775069
best.pt
YcvECxtXoxQ
9
00:08
Trunk
369.724915
380.062592
1,882.522705
1,395.134644
0.67327
best.pt
YcvECxtXoxQ
9
00:08
Back-windshield
454.606384
89.913666
1,896.951416
771.184814
0.660792
best.pt
YcvECxtXoxQ
9
00:08
Back-wheel
2,222.596436
1,261.0625
2,789.195801
2,157.524902
0.629353
best.pt
YcvECxtXoxQ
9
00:08
Back-window
2,294.748779
246.551697
2,536.818604
673.102783
0.601141
best.pt
YcvECxtXoxQ
9
00:08
Fender
3,197.279785
1,054.506592
3,368.470215
1,480.523071
0.467758
best.pt
YcvECxtXoxQ
9
00:08
Mirror
3,063.696289
719.34137
3,264.822266
935.87677
0.453605
best.pt
YcvECxtXoxQ
9
00:08
Trunk
363.995544
776.621155
1,827.738525
1,390.544434
0.422932
best.pt
YcvECxtXoxQ
10
00:09
Mirror
3,070.718262
688.364868
3,250.776123
838.575806
0.939525
best.pt
YcvECxtXoxQ
10
00:09
Front-wheel
3,069.387451
1,120.024902
3,340.977539
1,695.765137
0.702419
best.pt
YcvECxtXoxQ
10
00:09
License-plate
602.036133
795.196289
1,136.849365
1,044.465454
0.676904
best.pt
End of preview. Expand in Data Studio

Video Object Detection Index

NYU AI Spring 2026 — Assignment 2

This repository contains an object-detection database (index) generated from a video using a YOLO-based detection pipeline.
The dataset enables image-to-video semantic retrieval by matching detected object components between query images and indexed video frames.


Source Data

  • Video processed: Toyota RAV4 review video
  • Frame sampling rate: 1 FPS
  • Detection model: YOLOv8 (fine-tuned car-parts model)
  • Detector weights: best.pt

Dataset Schema

Each record represents a single detection.

| Column | Type | Description | | video_id | string | Unique YouTube video identifier | | frame_index | int | Frame number extracted from video | | timestamp | string | Timestamp in MM:SS format | | class_label | string | Detected car component | | x_min | float | Bounding box left coordinate | | y_min | float | Bounding box top coordinate | | x_max | float | Bounding box right coordinate | | y_max | float | Bounding box bottom coordinate | | confidence_score| float | Model confidence score | | detector_name | string | Detection model used |

Example entry:

video_id: YcvECxtXoxQ frame_index: 1 timestamp: 00:00 class_label: Front-wheel confidence_score: 0.95


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