Update download link (#339) Mar 9, 2024 setup.cfg update md5 and size; fix np.ndarray mypy errors (#147) Jun 29, 2021 setup.py Updates to scripts, fixing minor bugs in segmentation evaluation, add… Mar 30, 2022 BDD100K is a diverse driving dataset for heterogeneous multitask learning....
We provide documents and tools for inspection, preparation, and evaluation of the BDD100K dataset. Data Download You can simply log in and download the data in your browser after agreeing to BDD100K license. Visualization We provides scripts to parse and visualize the labels, and a tool to dis...
Developers can download theBDD100K self-driving dataset hereand read more about it inthis academic paper. Each video in the BDD100K self-driving dataset is about 40 seconds long and are viewed in 720p at 30 frames per second. According to the researchers, the videos were collected from about...
Download BDD dataset Please visit BDD100K for details. Training Download pretrained weights See weights readme for detail. Download pretrained backbone wegiths from Google Drive or Baidu Drive Move downloaded file darknet53_weights_pytorch.pth to wegihts folder in this project. Modify training param...
Dataset Path (optional) Pre-processing Download Pre-trained Models (VOC) Train Test Produce Detection Information References MobileNet-SSD and MobileNetV2-SSD/SSDLite with PyTorch Object Detection with MobileNet-SSD, MobileNetV2-SSD/SSDLite on VOC, BDD100K Datasets. ...
Figure 1. Image samples from BDD100K dataset, in which a great variability (occlusion, bad weather, glare, low light, low contrast, light reflection, blur...) can be noticed. Therefore, our aim was to train some YOLOv3 and YOLOv4 variants with BDD100K and to compare the performance of...
if__name__=='__main__':config={"datasets":"COCO","img_path":"E:/CODE/deyi/dataset/bdd100k/iamges/100k/train","label":"E:/CODE/deyi/dataset/bdd100k/labels_coco/bdd100k_labels_images_det_coco_train.json","img_type":".jpg","manipast_path":"./","output_path":"E:/CODE/deyi...
bdd100k bdd100k Discussions Sort by:Latest activity Label Filter Discussions 🙏 Metadata for the 10k dataset hutecaskedMar 12, 2021inQ&A· Answered 12
Download the training data Change the dataset root directory 'root' in src/lib/cfg/data.json and 'data_dir' in src/lib/opts.py Run: sh experiments/all_dla34.sh Tracking The default settings run tracking on the validation dataset from 2DMOT15. Using the DLA-34 baseline model, you can ...