Related Objects of Interest: ==============================, * auto-orientation of pixel data (with exif-orientation stripping), the following pre-processing was applied to each image:, * annotate, and create datasets, * collaborate with your team on computer vision projects, * export, train, and deploy computer vision models, * use active learning to improve your dataset over time, * 50% probability of horizontal flip, * collect & organize images, * equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise, upside-down
1 - 30 of 100k+
by sanu
87 images 496 classes
pipe yellow (1") CPVC PRO 45 DEG ELBOW (1") CPVC PRO COUPLER SDR 11 (1") CPVC PRO F.A.P.T SDR 11 (1") CPVC PRO PIPE CTS SDR11 5M (1") CPVC PRO TEE SDR 11 (1-1/4") CPVC PRO 45 DEG ELBOW (1-1/4") CPVC PRO 90 DEG ELBOW (1-1/4") CPVC PRO COUPLER SDR 11 (1-1/4") CPVC PRO F.A.P.T SDR 11 (1-1/4") CPVC PRO PIPE CTS SDR 11 5M (1-1/4") CPVC PRO TEE SDR 11 (1-1/4"x1") CPVC PRO COUPLER SDR 11 (1-1/4"x1") CPVC PRO TEE SDR 11 (3/4") CPVC PRO M.A.B.T SDR 11 (3/4") CPVC PRO PIPE CTS SDR 11 5M (3/4"x1/2") CPVC PRO BRS FPT 90 ELB (3/4"x1/2") CPVC PRO BRS FPT TEE SDR 11 (Brass)
by Class
1064 images 251 classes
aeroplane boat ship 1000 kilometer class cruise missile 1978 missile 1978 mission 2P25 TEL with 3 3M9 missiles of the surface- to-air Ballistic missile Russia Ballistic missiles:seoul miltary Brahmos DRDO successfully tests Agni Falcon heavy rocket launch Ghana HSTOV military vehicle Harpoon Russian kalibr Missile Harpoon and Russian kalibr missile Harpoon missiles India"s deadly missile India's missiles India's supersonic missile launched
by Yolo
122 images 122 classes
All motor vehicles prohibited Animals Axle load limit Barrier Blind persons likely on road ahead Built-up area Bullock cart and hand cart prohibited Bullock cart prohibited Bump Chevron Children Compulsory ahead Compulsory ahead or turn left Compulsory ahead or turn right Compulsory cycle track Compulsory keep left Compulsory minimum speed Compulsory sound horn Compulsory turn left Compulsory turn left ahead
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
215 images 6 classes
by akash
781 images 209 classes
ADOPT A HIGHWAY (ADOT)_D14-101 ADVANCE GUIDE 1 LINE 2 LINE DESTINATION DISTANCE_E1-102A ADVANCE STREET NAME (1-2-3 LINE)_D3-(2_2R_2S) ADVANCE TURN ARROW AUXILIARY - 90 DEGREE - INTERSTATE_M5-1 ADVANCE TURN ARROW AUXILIARY - 90 DEGREE_M5-1 AHEAD (PLAQUE)_R3-17AP AHEAD (PLAQUE)_W16-9P AIRPORT_I-5 ARM_BRIDGE ARM_CANTILEVER ARM_DOUBLEMAST ARM_SINGLEMAST ARM_SPANWIRE ARM_STEELDOUBLE ARM_STEELSINGLE BE PREPARED TO STOP_W3-4 BEGIN HIGHER FINES ZONE_R2-10 BEGIN_M4-14 BICYCLE (SYMBOL)_W11-1 BICYCLE OR PEDESTRIAN (SYMBOL)_W11-15
by test
200 images 22 classes
* 50% probability of horizontal flip * 50% probability of vertical flip * 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 * Resize to 600x600 (Fit (white edges)) * 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 ============================== Chocolates are annotated in YOLOv8 format. For state of the art Computer Vision training notebooks you can use with this dataset, Roboflow is an end-to-end computer vision platform that helps you The dataset includes 267 images. The following augmentation was applied to create 5 versions of each source image: The following pre-processing was applied to each image: This dataset was exported via roboflow.com on June 4, 2023 at 12:27 PM GMT To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com
by Garbage
781 images 209 classes
ADOPT A HIGHWAY (ADOT)_D14-101 ADVANCE GUIDE 1 LINE 2 LINE DESTINATION DISTANCE_E1-102A ADVANCE STREET NAME (1-2-3 LINE)_D3-(2_2R_2S) ADVANCE TURN ARROW AUXILIARY - 90 DEGREE - INTERSTATE_M5-1 ADVANCE TURN ARROW AUXILIARY - 90 DEGREE_M5-1 AHEAD (PLAQUE)_R3-17AP AHEAD (PLAQUE)_W16-9P AIRPORT_I-5 ARM_BRIDGE ARM_CANTILEVER ARM_DOUBLEMAST ARM_SINGLEMAST ARM_SPANWIRE ARM_STEELDOUBLE ARM_STEELSINGLE BE PREPARED TO STOP_W3-4 BEGIN HIGHER FINES ZONE_R2-10 BEGIN_M4-14 BICYCLE (SYMBOL)_W11-1 BICYCLE OR PEDESTRIAN (SYMBOL)_W11-15
by Road Traffic
9866 images 398 classes
complementary--accident-area--g3 complementary--both-directions--g1 complementary--buses--g1 complementary--chevron-left--g1 complementary--chevron-left--g2 complementary--chevron-left--g3 complementary--chevron-left--g4 complementary--chevron-left--g5 complementary--chevron-right--g1 complementary--chevron-right--g3 complementary--chevron-right--g4 complementary--chevron-right--g5 complementary--chevron-right-unsure--g6 complementary--distance--g1 complementary--distance--g2 complementary--distance--g3 complementary--except-bicycles--g1 complementary--extent-of-prohibition-area-both-direction--g1 complementary--go-left--g1 complementary--go-right--g1
by Marco
9560 images 52 classes
* 50% probability of horizontal flip * 50% probability of vertical flip * 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 * Random Gaussian blur of between 0 and 1.75 pixels * Random brigthness adjustment of between -25 and +25 percent * Random exposure adjustment of between -15 and +15 percent * Random rotation of between -10 and +10 degrees * Random shear of between -2° to +2° horizontally and -2° to +2° vertically * Randomly crop between 0 and 15 percent of the image * 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 29 30
by dev1
80 images 29 classes
* 50% probability of horizontal flip * 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 * Random rotation of between -15 and +15 degrees * 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 unstructured image data * use active learning to improve your dataset over time 20 21 22 23 24 25 26 27
by Fun stuff
4793 images 93 classes
* 50% probability of horizontal flip * 50% probability of vertical flip * 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 * 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
1994 images 37 classes
* 50% probability of horizontal flip * 50% probability of vertical flip * Auto-orientation of pixel data (with EXIF-orientation stripping) * Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise * Resize to 180x300 (Stretch) * Salt and pepper noise was applied to 1 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 melon
7221 images 30 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 * Random Gaussian blur of between 0 and 2.5 pixels * Resize to 640x640 (Stretch) * annotate, and create datasets * collaborate with your team on computer vision projects * 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 26 27 29 ============================== Axe Bazooka Gun Katana
by dsad
7635 images 86 classes
object * 50% probability of horizontal flip * 50% probability of vertical flip * Auto-orientation of pixel data (with EXIF-orientation stripping) * Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise * Random Gaussian blur of between 0 and 1.5 pixels * Random brigthness adjustment of between -25 and +25 percent * Random brigthness adjustment of between -30 and +30 percent * Random rotation of between -23 and +23 degrees * Resize to 640x640 (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 28 29 30
3006 images 38 classes
* 50% probability of horizontal flip * Auto-orientation of pixel data (with EXIF-orientation stripping) * Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise * Random rotation of between -15 and +15 degrees * Randomly crop between 0 and 20 percent of the image * Resize to 416x416 (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 23 24 25 26 27 28 29 30
3006 images 38 classes
* 50% probability of horizontal flip * Auto-orientation of pixel data (with EXIF-orientation stripping) * Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise * Random rotation of between -15 and +15 degrees * Randomly crop between 0 and 20 percent of the image * Resize to 416x416 (Stretch) 13 14 15 16 17 18 19 20 21 22 23 24 25 26
by ingredients
9335 images 38 classes
* 50% probability of horizontal flip * Auto-orientation of pixel data (with EXIF-orientation stripping) * Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise * Random rotation of between -15 and +15 degrees * Randomly crop between 0 and 20 percent of the image * Resize to 416x416 (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 23 24 25 26 27 28 29 30
by Deneme
3362 images 694 classes
* Auto-contrast via contrast stretching * 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 * Random shear of between -14° to +14° horizontally and -15° to +15° vertically * Resize to 800x800 (Stretch) * Salt and pepper noise was applied to 1.13 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 100 101 102 103 104 105 106 107
by Deneme
3256 images 692 classes
* Auto-contrast via contrast stretching * 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 * Random shear of between -14° to +14° horizontally and -15° to +15° vertically * Resize to 800x800 (Stretch) * Salt and pepper noise was applied to 1.13 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 100 101 102 103 104 105 106 107
by nina
245 images 31 classes
chocolate * 50% probability of horizontal flip * 50% probability of vertical flip * 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 * Random Gaussian blur of between 0 and 0.5 pixels * Random brigthness adjustment of between -16 and +16 percent * Random exposure adjustment of between -6 and +6 percent * Resize to 600x600 (Fit (white edges)) 15 16 17 18 19 20 21 ============================== Chocolates are annotated in YOLO v5 PyTorch format. It includes 267 images. The following augmentation was applied to create 5 versions of each source image:
by chocolate
244 images 31 classes
* 50% probability of horizontal flip * 50% probability of vertical flip * 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 * Random Gaussian blur of between 0 and 0.5 pixels * Random brigthness adjustment of between -16 and +16 percent * Random exposure adjustment of between -6 and +6 percent * Resize to 600x600 (Fit (white edges)) -black chocolate -brown chocolate -gift chocolate -wave chocolate -white chocolate 15 16 17 18 19 20 21
by yolo
200 images 23 classes
* 50% probability of horizontal flip * 50% probability of vertical flip * 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 * Resize to 600x600 (Fit (white edges)) * 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 ============================== Chocolates Chocolates are annotated in YOLOv8 format. For state of the art Computer Vision training notebooks you can use with this dataset, Roboflow is an end-to-end computer vision platform that helps you The dataset includes 267 images. The following augmentation was applied to create 5 versions of each source image: The following pre-processing was applied to each image: This dataset was exported via roboflow.com on June 4, 2023 at 12:27 PM GMT
by York
246 images 27 classes
* 50% probability of horizontal flip * 50% probability of vertical flip * 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 * Random Gaussian blur of between 0 and 0.5 pixels * Random brigthness adjustment of between -16 and +16 percent * Random exposure adjustment of between -6 and +6 percent * Resize to 600x600 (Fit (white edges)) 15 16 17 18 19 20 21 ============================== Chocolates are annotated in YOLO v5 PyTorch format. Dark Marzipan It includes 267 images. Milk California Brittle
436 images 126 classes
1978 mission 2P25 TEL with 3 3M9 missiles of the surface- to-air Ballistic missile Russia DRDO successfully tests Agni Ghana India"s deadly missile India's supersonic missile launched Indian military vehicle Indian missile Indian missile launch Indian missile ready to be launched Iran missile Iran missile launch Iranian missile launch Launch of Ballistic missile NASA launch photos North Korea says it fired railway North koreas latest missile launch North koreas missile Nuclear submarine critical test
by Mostra
41773 images 401 classes
complementary--accident-area--g3 complementary--both-directions--g1 complementary--buses--g1 complementary--chevron-left--g1 complementary--chevron-left--g2 complementary--chevron-left--g3 complementary--chevron-left--g4 complementary--chevron-left--g5 complementary--chevron-right--g1 complementary--chevron-right--g3 complementary--chevron-right--g4 complementary--chevron-right--g5 complementary--chevron-right-unsure--g6 complementary--distance--g1 complementary--distance--g2 complementary--distance--g3 complementary--except-bicycles--g1 complementary--extent-of-prohibition-area-both-direction--g1 complementary--go-left--g1 complementary--go-right--g1
by TEST 1
2254 images 35 classes
chicken train #-Healthy-and-Sick-Chicken-Detection->-2023-02-04-2:29pm *-50%-probability-of-horizontal-flip *-50%-probability-of-vertical-flip *-Auto-orientation-of-pixel-data-(with-EXIF-orientation-stripping) *-Equal-probability-of-one-of-the-following-90-degree-rotations:-none *-Random-exposure-adjustment-of-between--25-and-+25-percent *-Resize-to-416x416-(Stretch) *-annotate *-collaborate-with-your-team-on-computer-vision-projects *-collect-&-organize-images *-export *-understand-and-search-unstructured-image-data *-use-active-learning-to-improve-your-dataset-over-time 1WOC-are-annotated-in-Tensorflow-Object-Detection-format. 2024-at-10:31-AM-GMT ============================== For-state-of-the-art-Computer-Vision-training-notebooks-you-can-use-with-this-dataset Healthy-and-Sick-Chicken-Detection---v18-2023-02-04-2:29pm
1 - 30 of 100k+