Google Drive 76.0.3 download the last version for windows

This repository is designed to provide an open-source dataset for license plate detection and recognition, described in 《Towards End-to-End License Plate Detection and Recognition: A Large Dataset and Baseline》. The test set contains six parts: DB(ccpd_db/), Blur(ccpd_blur), FN(ccpd_fn), Rotate(ccpd_rotate), Tilt(ccpd_tilt), Challenge(ccpd_challenge). The column 'AP' shows the precision on all the test set. We provide baseline methods for recognition by appending a LP recognition model Holistic-CNN (HC) (refer to paper 'Holistic recognition of low quality license plates by cnn using track annotated data') to the detector.

If you want to provide more baseline results or have problems about the provided results. A LP recognition is correct if and only if all characters in the LP number are correctly recognized. The bounding box is considered to be correct if and only if its IoU with the ground truth bounding box is more than 70% (IoU > 0.7). For each image, the detector outputs only one bounding box. Detectors are allowed to predict only one bounding box for each image.ĭetection. Therefore, we do not consider recall and concerntrate on precision. We add a new energy vehicle sub-dataset (CCPD-Green) which has an eight-digit license plate number.Īs each image in CCPD contains only a single license plate (LP). Sub-datasets (CCPD-DB, CCPD-Blur, CCPD-FN, CCPD-Rotate, CCPD-Tilt, CCPD-Challenge) in CCPD are exploited for test.

Images in CCPD-Base is split to train/val set. The split file is available under 'split/' folder.

It can be downloaded from and extract by (tar xf ): (If you are benefited from this dataset, please cite our paper.) We are confident that images in subsets of CCPD is much more challenging than before with over 300k images and refined annotations. CCPD (Chinese City Parking Dataset, ECCV) UPdate on.

Google Drive 76.0.3 download the last version for windows