Related Objects of Interest: visit https://github.com/roboflow/notebooks, ==============================, * collaborate with your team on computer vision projects, * export, train, and deploy computer vision models, * understand and search unstructured image data, * annotate, and create datasets, * collect & organize images, * 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
Top Https Datasets and Models
The datasets below can be used to train fine-tuned models for https detection. You can explore each dataset in your browser using Roboflow and export the dataset into one of many formats.
At the bottom of this page, we have guides on how to train a model using the https datasets below.
9949 images 39 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Random Gaussian blur of between 0 and 5 pixels * Random exposure adjustment of between -20 and +20 percent * Random rotation of between -10 and +10 degrees * Random shear of between -15° to +15° horizontally and -15° to +15° 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 23 24 25 26 27 28 29 30
9440 images 14 classes
object * 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 ============================== Clothes - v2 2023-10-15 8:28pm 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 This dataset was exported via roboflow.com on November 28, 2023 at 10:44 AM GMT To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com visit https://github.com/roboflow/notebooks
by bcvt
9760 images 33 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Random Gaussian blur of between 0 and 1.5 pixels * Random rotation of between -15 and +15 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 21 22 23 24 25 26 27 28 29 30
by Flash0007
4181 images 55 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 Work
4514 images 194 classes
* 50% probability of horizontal flip * Auto-contrast via histogram equalization * 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 * Random brigthness adjustment of between -25 and +25 percent * Random exposure adjustment of between -16 and +16 percent * Random rotation of between -12 and +12 degrees * Random shear of between -12° to +12° horizontally and -10° to +10° vertically * Randomly crop between 0 and 20 percent of the bounding box * 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 100 101 102
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
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
4240 images 46 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 grad project
523 images 40 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Resize to 640x640 (Stretch) * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data 1 19 2 20 21 23 3 4 5 6 7 8 9 ==============================
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 k66a4
2914 images 59 classes
* Auto-contrast via contrast stretching * 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
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
by uni
1094 images 4 classes
3314 images 58 classes
* Auto-contrast via contrast stretching * 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 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
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
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
by Test ES
1493 images 37 classes
* Random rotation of between -15 and +15 degrees * Random shear of between -15° to +15° horizontally and -15° to +15° vertically * 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 21 22 23 24 25 26 27 28 29 30 31
2564 images 58 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Resize to 1000x1000 (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 Thanh
7640 images 24 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 .... are annotated in YOLOv8 format. 17 18 19 20 21 22 23 ============================== For state of the art Computer Vision training notebooks you can use with this dataset, No image augmentation techniques were applied. Roboflow is an end-to-end computer vision platform that helps you TDL_final - v3 2024-04-14 3:28pm The dataset includes 7664 images.
4466 images 12 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 Skin Problems Detection - v8 2024-03-12 12:48pm This dataset was exported via roboflow.com on March 13, 2024 at 6:20 AM GMT visit https://github.com/roboflow/notebooks
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