Related Objects of Interest: ==============================, the following pre-processing was applied to each image:, * auto-orientation of pixel data (with exif-orientation stripping), * export, train, and deploy computer vision models, visit https://github.com/roboflow/notebooks, * annotate, and create datasets, * collaborate with your team on computer vision projects, * collect & organize images, * understand and search unstructured image data, * use active learning to improve your dataset over time
Top Resize Computer Vision Models
The models below have been fine-tuned for various resize detection tasks. You can try out each model in your browser, or test an edge deployment solution (i.e. to an NVIDIA Jetson). You can use the datasets associated with the models below as a starting point for building your own resize detection model.
At the bottom of this page, we have guides on how to count resizes in images and videos.
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
4270 images 29 classes
ambulance bus motorcycle rickshaw * 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 ============================== 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 The dataset includes 4263 images. The following pre-processing was applied to each image: This dataset was exported via roboflow.com on June 19, 2023 at 1:18 PM GMT
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 gj pw
3274 images 21 classes
object * 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 ============================== Car-parts are annotated in YOLOv8 Oriented Object Detection format. CarPartBB - v1 2023-10-19 1:12pm 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 The dataset includes 3291 images. The following pre-processing was applied to each image: This dataset was exported via roboflow.com on February 12, 2024 at 11:07 AM GMT To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com
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 Test
4176 images 43 classes
object * Auto-orientation of pixel data (with EXIF-orientation stripping) * Random rotation of between -45 and +45 degrees * Resize to 640x640 (Stretch) * annotate, and create datasets * 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 20 21 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 Mini Project
40 images 33 classes
battery computer laptop mobile remote television watch * 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
by Laxav
1800 images 27 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 0 13 16 18 21 25 3 5 ============================== A American Sign Language Letters - v1 v1 For state of the art Computer Vision training notebooks you can use with this dataset,
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
by ECE4300
1605 images 24 classes
object * 50% probability of horizontal flip * 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 ============================== Animal detect - v2 2023-04-25 3:38pm Animals are annotated in YOLOv8 format. For state of the art Computer Vision training notebooks you can use with this dataset, Person dataset - v3 2023-11-16 1:52am Roboflow is an end-to-end computer vision platform that helps you The dataset includes 269 images. The following augmentation was applied to create 3 versions of each source image: The following pre-processing was applied to each image: This dataset was exported via roboflow.com on April 25, 2023 at 10:09 AM GMT To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com
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 MY
9880 images 60 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Random rotation of between -20 and +20 degrees * 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 20 21 22 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) * 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 Thavcayena
5122 images 41 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Grayscale (CRT phosphor) * 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 0 1 2 3 4 5 6 7 8 9 ==============================
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 college
3480 images 27 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Random Gaussian blur of between 0 and 2.5 pixels * Random brigthness adjustment of between -25 and +25 percent * Resize to 640x640 (Stretch) * Salt and pepper noise was applied to 14 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 ============================== For state of the art Computer Vision training notebooks you can use with this dataset, Road Sign Detector - v7 Add blur and noise Roboflow is an end-to-end computer vision platform that helps you
by yolo
600 images 17 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 ============================== Fcsdq 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 600 images. The following pre-processing was applied to each image: This dataset was exported via roboflow.com on October 11, 2023 at 8:42 AM GMT To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com visit https://github.com/roboflow/notebooks wdsaf - v1 2023-10-11 3:41pm
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 KUST
1203 images 27 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Grayscale (CRT phosphor) * Resize to 640x640 (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 . 0 2 5 6 7 8 ============================== For state of the art Computer Vision training notebooks you can use with this dataset, LCD - v14 2023-10-13 2:03pm LCD-Display are annotated in YOLOv8 format.
by SREEVISHAK V
888 images 5 classes
by obsessedfish
279 images 136 classes
* Auto-contrast via adaptive equalization * 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 100 101 102 103 104 105 106 107 108 109 110
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 ocrdetection
325 images 132 classes
dot * 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 - 0 1 19 2 20 21 22 23 24 25
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