Related Objects of Interest: ==============================, the following pre-processing was applied to each image:, * auto-orientation of pixel data (with exif-orientation stripping), * collaborate with your team on computer vision projects, * annotate, and create datasets, * collect & organize images, * export, train, and deploy computer vision models, * use active learning to improve your dataset over time, roboflow is an end-to-end computer vision platform that helps you, no image augmentation techniques were applied.
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
by go4av05
8659 images 40 classes
* Random Gaussian blur of between 0 and 2.5 pixels * Random brigthness adjustment of between -25 and +25 percent * Random exposure adjustment of between -25 and +25 percent * 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 17 18 19 20 21 22 23 24 25 26
880 images 11 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Resize to 416x416 (Stretch) 10 9 ============================== Ingredientsdataset are annotated in YOLO v5 PyTorch format. It includes 905 images. No image augmentation techniques were applied. The following pre-processing was applied to each image: This dataset was exported via roboflow.ai on May 30, 2021 at 10:39 AM GMT ingredients_dataset - v4 ingredients_data_meet_add
by sr
840 images 8 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Resize to 896x896 (Stretch) ============================== Fruits and Thumb detection - v5 v5 for yolov4 darknet Fruits-and-Thumb are annotated in YOLO v5 PyTorch format. It includes 859 images. The following pre-processing was applied to each image: This dataset was exported via roboflow.ai on April 15, 2022 at 7:08 AM GMT
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
8355 images 6 classes
by testing
680 images 8 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Resize to 640x640 (Stretch) ============================== Fruits and Thumb detection - v1 yolov5_v1 Fruits-and-Thumb are annotated in YOLO v5 PyTorch format. It includes 687 images. The following pre-processing was applied to each image: This dataset was exported via roboflow.ai on March 4, 2022 at 12:38 PM GMT
by yolov5
2587 images 10 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Resize to 640x640 (Stretch) 9 ============================== HanYang - v2 Yolov5 New It includes 2755 images. No image augmentation techniques were applied. The following pre-processing was applied to each image: This dataset was exported via roboflow.ai on March 30, 2022 at 5:53 AM GMT Tree are annotated in YOLO v5 PyTorch format.
by sugi1
760 images 262 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 100 101 102 103 104 105 106 107 108 109 18 19 20
by test
188 images 25 classes
* annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * use active learning to improve your dataset over time 17 18 19 20 21 22 23 24 26 ============================== For state of the art Computer Vision training notebooks you can use with this dataset, No image augmentation techniques were applied. Roadblocks are annotated in YOLO v5 PyTorch format. Roboflow is an end-to-end computer vision platform that helps you The dataset includes 213 images.
by MedRobos
960 images 15 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 ============================== 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 Surgical-tools are annotated in YOLO v5 PyTorch format. The dataset includes 972 images. This dataset was exported via roboflow.com on March 11, 2023 at 12:50 PM GMT To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com surgical tool detection - v3 2023-03-11 6:19pm visit https://github.com/roboflow/notebooks
by AI
2240 images 34 classes
object * 50% probability of horizontal flip * 50% probability of vertical flip * Auto-orientation of pixel data (with EXIF-orientation stripping) * Resize to 640x640 (Stretch) * annotate, and create datasets * annotate, and create datasets * collect & organize images * annotate, and create datasets * understand and search unstructured image data * 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 23 24 24 25 26
by IC
220 images 29 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 ============================== For state of the art Computer Vision training notebooks you can use with this dataset,
by dhruti
1720 images 26 classes
* 50% probability of horizontal flip * Auto-orientation of pixel data (with EXIF-orientation stripping) * Random Gaussian blur of between 0 and 1.25 pixels * Random brigthness adjustment of between -25 and +25 percent * Random rotation of between -5 and +5 degrees * Random shear of between -5° to +5° horizontally and -5° to +5° vertically * Randomly crop between 0 and 20 percent of the image * Resize to 416x416 (Stretch) 15 16 17 18 19 20 21 22 23 24 25 ==============================
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 Fort1
5306 images 28 classes
head person player * Auto-orientation of pixel data (with EXIF-orientation stripping) * 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 unstructured image data * use active learning to improve your dataset over time 0 1 16 18 19 20 ============================== Fortnite Player Tracker - v1 2024-02-10 10:30pm It includes 280 images.
by HibaB
3084 images 18 classes
10 11 12 13 14 7 8 9 ============================== BCCD - v3 raw Card-Types are annotated in YOLO v5 PyTorch format. It includes 8992 images. No image augmentation techniques were applied. The following pre-processing was applied to each image: This dataset was exported via roboflow This dataset was exported via roboflow.ai on February 24, 2021 at 10:05 AM GMT This dataset was exported via roboflow.ai on October 16, 2020 at 3:14 PM GMT Uno Cards - v2 raw
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
by My workspace
560 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 11 12 13 14 15 16 17 18 19 20 21 22 23
1612 images 31 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * 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 19 20 21 22 23 24 25 26 27 28 29 30
by Kev
3720 images 30 classes
crack * 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 ============================== Blockage Broken Broken are annotated in YOLO v5 PyTorch format. Collapsed Dripper For state of the art Computer Vision training notebooks you can use with this dataset, Fractures Gas-Pipe Infiltration Pile Pitch-Fiber Roboflow is an end-to-end computer vision platform that helps you
1425 images 8 classes
car * collaborate with your team on computer vision projects ============================== Roboflow is an end-to-end computer vision platform that helps you This dataset was exported via roboflow.com on November 25, 2023 at 4:44 PM GMT Vehicle Detection YOLO V5 - v1 YOLO v5 vehicle detection heavy vehicle lightvehicle