Related Objects of Interest: * annotate, and create datasets, * collaborate with your team on computer vision projects, * collect & organize images, * export, train, and deploy computer vision models, * understand and search unstructured image data, * use active learning to improve your dataset over time, ==============================, the following pre-processing was applied to each image:, to find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com, visit https://github.com/roboflow/notebooks
by James Mixon
5399 images 73 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Random rotation of between -5 and +5 degrees * Randomly crop between 0 and 30 percent of the image * Resize to 640x352 (Fit within) * Salt and pepper noise was applied to 0 percent of pixels * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 0 1 10 100 1000 10th Spot 11 12 13
by hoang quang
1452 images 1513 classes
.6R1.6B-Argiphysol (H/12vỉ x 5v nang mềm) -Hộp- Hà tây 10R1 10R1-5B-Ospay Baby (Lọ 15ml) -Lọ- Trường Thọ 10R1.10C-KĐR Sensodyne-Fresh Mint (Tub 100g)-Thái Lan 10R1.11B-Kamazitap10g Celia- (Hadophar)-tuýp 10R1.11D-KĐR Sensodyne - Gentle Whitening 10R1.12B-Kem nghệ Thái dương 10R1.13A-Kem em bé 20g CVI 10R1.13C-KĐR Sensodyne RAPID Action--giảm ê buốt 10R1.14Aa-Kem nghệ YooSun 25g 10R1.14Ca-KĐR Lacalut aktiv - Đỏ 10R1.15B-KĐR Thái Dương tub 150g 10R1.15D-KĐR Ngọc Châu Tub 125g- Hoa Linh 10R1.1D-Tinh Dầu Tràm Bé Thơ (Lọ 100ml) 10R1.2D-Remos(xịt muỗi) lọ 70ml - Rohto 10R1.3D-Tinh dầu Tràm Bé Thơ 50ml 10R1.4A-Sữa tắm Tây Thi (Lọ 200g) -Hộp- Thái Dương 10R1.4Ca-Zuchi Family (Giầy) (Lọ 50ml - 10lo/Cầu) - Hoa Linh 10R1.5D-Listerine CoolMint (Chai 250ml)-chai-Thái Lan 10R1.611Bc-Xịt mũi Vinasat NL 75ml (xanh)
1158 images 57 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Resize to 640x640 (Stretch) * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 1 10(10pin) 10(4pin) 11 13 14 1400 15 16 17 18 19
by HADJEM
1238 images 103 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Random brigthness adjustment of between -1 and +1 percent * Random rotation of between -1 and +1 degrees * Random shear of between -1° to +1° horizontally and -0° to +0° vertically * Resize to 640x640 (Stretch) * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 22 23 24 25 26 27 28 29 30
2162 images 69 classes
1-U-turn 10-No-entry 11-Weight-limit-sign-5T 12-Weight-limit-sign-30T 13-Height-limit-sign-2.0m 14-Height-limit-sign-3.0m 15-Height-limit-sign-4.0m 16-Height-limit-sign-5.0m 17-Height-limit-sign-6.0m 18-Speed-Limit-20 19-Speed-Limit-30 2-Keep-right 21-Speed-Limit-50 22-Speed-Limit-60 23-Speed-Limit-70 24-Speed-Limit-80 25-Speed-Limit-90 26-Speed-Limit-110 27-No-Entry-for-Vehicles-Exceeding-5T 28-Heavy-vehicles-no-driving-on-the-right-lane
by ElektroTeile
1237 images 144 classes
* annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 100 101 102 103 104 105 106 107 108 109 110 111 112 113
by traffcsgn
1392 images 33 classes
0-tramvay-10 1-tramvay-15 10-may-encounter-motorcycle 11-caution 12-may-encounter-car 13-no-entry 14-forward-left 15-forward-right 16-light-ahead 17-intersection 18-vehicles-not-allowed 19-no-parking-1 2-tramvay-20 20-no-parking-2 21-right 22-pass-on-the-right 23-no-turning-left 24-no-turning-right 25-stop 26-road-closed-to-traffic
3520 images 39 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Resize to 640x640 (Stretch) * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 19 20 21 22 23 24 25 26 27 28 29 30
1760 images 38 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Random shear of between -15° to +15° horizontally and -15° to +15° vertically * Resize to 416x416 (Stretch) * Salt and pepper noise was applied to 4 percent of pixels * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 21 22 23 24 25 26 27 28 29 30
3279 images 28 classes
* annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 17 18 19 20 21 22 23 24 25 26 27 ============================== For state of the art Computer Vision training notebooks you can use with this dataset, No image augmentation techniques were applied.
by Naer
8478 images 53 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Grayscale (CRT phosphor) * Random brigthness adjustment of between -25 and +25 percent * Random exposure adjustment of between -25 and +25 percent * Resize to 640x640 (Stretch) * Salt and pepper noise was applied to 2 percent of pixels * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 24 25 26 27 28 29 30 31
by ttest
8487 images 54 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise, upside-down * Grayscale (CRT phosphor) * Resize to 416x416 (Stretch) * Salt and pepper noise was applied to 5 percent of pixels * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 22 23 24 25 26 27 28 29 30
42 images 3373 classes
"capacitor jumper" CJ1 "capacitor jumper" CJ2 "component text" "-309 LL6" "component text" "0 N" "component text" "0001 5293 170A" "component text" "021 LDBM N389" "component text" "0821-1X1T-43-F 1402 WM" "component text" "0833 LTC2274 UJ BT267910" "component text" "085811 B4T EHCR" "component text" "0N 5C" "component text" "1 2 3 4" "component text" "1 2" "component text" "100 CFK 7BD" "component text" "100 CFK- 7BD" "component text" "100 VFK- 87" "component text" "100 VFK- 8R7" "component text" "106C 43JJ2" "component text" "107A 938H4" "component text" "12-000" "component text" "15 203"
by nci
934 images 75 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 0 1 10 11 12 13 14 15 16 17 18 19 2
by notebook
40 images 4491 classes
"capacitor jumper" CJ1 "capacitor jumper" CJ2 "component text" " CC BE 10000000" "component text" "-309 LL6" "component text" "0 1 2 3 4 5 6 7" "component text" "0 N" "component text" "0001 5293 170A" "component text" "0123456789ABCDEF" "component text" "021 LDBM N389" "component text" "0821-1X1T-43-F 1402 WM" "component text" "0833 LTC2274 UJ BT267910" "component text" "085811 B4T EHCR" "component text" "1 2 3 4 5 6 7 8" "component text" "1 2 3 4" "component text" "1 2 3" "component text" "1 2" "component text" "100 25V UT" "component text" "100 50V UT" "component text" "100 6V" "component text" "100 CFK 7BD"
132 images 11 classes
1473 images 59 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 18 19 20 21 22 23 24 25 26 27 28 29 30
by SnowWhite
200 images 85 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Resize to 160x160 (Stretch) * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 01 03 04 05 07 09 19 20 21 22 23 24
640 images 82 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Resize to 640x640 (Stretch) * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 19 20 21 22 23 24 25 26 27 28 29 30
by recipeVision
1995 images 47 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Random rotation of between -15 and +15 degrees * Random rotation of between -37 and +37 degrees * Salt and pepper noise was applied to 5 percent of pixels * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 22 23 24 25 26 27 28 29 30 31
by plural
3200 images 170 classes
* Resize to 640x640 (Stretch) * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 100 101 102 103 104 105 106 107 108 109 110 111 112
by plural
3200 images 170 classes
* Resize to 640x640 (Stretch) * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 100 101 102 103 104 105 106 107 108 109 110 111 112
by plural
2640 images 170 classes
* Resize to 640x640 (Stretch) * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 100 101 102 103 104 105 106 107 108 109 110 111 112
356 images 53 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Resize to 640x640 (Stretch) * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 19 20 21 22 23 24 25 26 27 28 29 30