Related Objects of Interest: * auto-orientation of pixel data (with exif-orientation stripping), ==============================, no image augmentation techniques were applied., the following pre-processing was applied to each image:, person, -{'xmin': 108, -{'xmin': 1081, -{'xmin': 1090, -{'xmin': 1097, -{'xmin': 1206
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Top 905 Datasets and Models
The datasets below can be used to train fine-tuned models for 905 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 905 datasets below.
45 images 2069 classes
mask person -0-0 -100-64878048780469 -1000-0022505626407 -1000-1762127875611 -1000-8264462809908 -1001-0032508127034 -1001-8777110212488 -1002-3880414131419 -1003-4712241544406 -1003-5545789548756 -1003-9399267094751 -1005-1809269702934 -1005-4692262573712 -1007-4300071058922 -1008-9999999999981 -1009-4100906134347 -1009-4150672768247 -1009-6934516720788
74 images 71 classes
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 Traffic
1958 images 1876 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 100 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 101
86 images 73 classes
529 images 4201 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 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 101 1010
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