git clone https://github.com/yangzhaonan18/yolov3_trafficSign_pytorch- Download detection(yolov3) weights: Baidu network disk link(234MB): https://pan.baidu.com/s/1BWySwi22nsFTB7-c0ualZA
download and put it at: ./checkpoints/yolov3_ckpt_33.pth
- Download classifier(CNN) weights: Baidu network disk link(43MB): https://pan.baidu.com/s/1Id65qVFrAp-S5G--57LG2Q
download and put it at: ./ALL_sign_data/checkpoints/
python3 detection_and_classification.pydetect the images in "./image_for_detect/Tinghua100K/", and the images with results will be saved in "./output", the "Tinghua100K_result.json" result will be saved in "./result/"
images with results:
cd Tinghua100K_data/python/
python3 my_result_classes.py
results is:
iou:0.5, size:[0,400), types:[w55, ...total 53...], accuracy:0.8845589434208381, recall:0.9304519337964154
iou:0.5, size:[0,32), types:[w55, ...total 53...], accuracy:0.8160990712074303, recall:0.885752688172043
iou:0.5, size:[32,96), types:[w55, ...total 53...], accuracy:0.9297398348652438, recall:0.9740492900277461
iou:0.5, size:[96,400), types:[w55, ...total 53...], accuracy:0.9261477045908184, recall:0.8672897196261682
iou:0.5, size:[0,400), types:w55, accuracy:0.9611650485436893, recall:0.908256880733945
iou:0.5, size:[0,400), types:p27, accuracy:0.9156626506024096, recall:0.9047619047619048
iou:0.5, size:[0,400), types:il80, accuracy:0.9746192893401016, recall:0.9746192893401016
iou:0.5, size:[0,400), types:i1, accuracy:0.8571428571428571, recall:1.0
iou:0.5, size:[0,400), types:il100, accuracy:0.89, recall:0.967391304347826
......
......
- Download pretrained weights(on COCO): darknet53.conv.74
cd ./weights
bash download_weights.sh
- Train YOLOv3 detection
cd ../
python3 train.py --data_config config/Tinghua100K.data --pretrained_weights weights/darknet53.conv.74
The YOLOv3 training weights will be saved in ./checkpoints/
- Download traffic sign data to train classifier Baidu network disk link: https://pan.baidu.com/s/133wOElvWHn0Fm4RzOGLk3w and unzip it in ALL_sign_data/ALL_data_in_2_train/
cd ./ALL_sign_data/
bash run.sh
The train weights will be saved in ./ALL_sign_data/checkpoints
- The data set is stored in folder : /headless/Desktop/yzn_file/DataSet_traffic_sign/ which contains 3 datasets:
- CCTSDB_changsha
- GTSDB
- Tinghua_100K
- each file contains three files(most important)
- images_jpg : jpg images
- labels: txt label for YOLOv3
- labels_xml: xml label for VOC dataset
- scripts
2_2voc_label.py : convert the three files "CCTSDB_changsha", "GTSDB", "Tinghua_100K" train and test label from .xml(VOC) to .txt(YOLOv3) and create the image path file of three datasets.
The "train.txt" and "test.txt" contain the images's absolute path will be saved in ./ALL_DATA
cd /headless/Desktop/yzn_file/DataSet_traffic_sign/
python3 2_2voc_label.py
cd ../yolov3_trafficSign_pytorch
# train from yolo pretrained weights:darknet53.conv.74
python3 train.py --pretrained_weights weights/darknet53.conv.74
or
# train from my pretrained weights:yolov3_ckpt_33.pth
python3 train.py --pretrained_weights checkpoints/yolov3_ckpt_33.pth
- Train logs
---- [Epoch 0/300, Batch 39/19133] ----
+------------+--------------+--------------+--------------+
| Metrics | YOLO Layer 0 | YOLO Layer 1 | YOLO Layer 2 |
+------------+--------------+--------------+--------------+
| grid_size | 38 | 76 | 304 |
| loss | 20.597389 | 15.203256 | 22.110357 |
| x | 0.153537 | 0.110538 | 0.065873 |
| y | 0.059418 | 0.069747 | 0.058901 |
| w | 2.156327 | 0.737079 | 0.113998 |
| h | 1.517446 | 0.609778 | 0.385179 |
| conf | 16.404194 | 13.595131 | 20.615255 |
| cls | 0.306469 | 0.080982 | 0.871151 |
| cls_acc | 100.00% | 100.00% | 100.00% |
| recall50 | 0.000000 | 0.000000 | 0.000000 |
| recall75 | 0.000000 | 0.000000 | 0.000000 |
| precision | 0.000000 | 0.000000 | 0.000000 |
| conf_obj | 0.283539 | 0.095890 | 0.186076 |
| conf_noobj | 0.138449 | 0.103401 | 0.168427 |
+------------+--------------+--------------+--------------+
Total loss 57.91100311279297
---- ETA 3:00:59.369194
path ['/headless/Desktop/yzn_file/DataSet_traffic_sign/CCTSDB_changsha/images_jpg/train/06006.jpg']
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