From 83c6eba700997eb826952e217b069b2779d0d26e Mon Sep 17 00:00:00 2001 From: Glenn Jocher Date: Wed, 20 Mar 2019 13:26:46 +0200 Subject: [PATCH] Update README.md --- README.md | 43 ++++++++++++++++++++++++++++++++++++++++--- 1 file changed, 40 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 0fe97933..1e26b8ee 100755 --- a/README.md +++ b/README.md @@ -84,11 +84,48 @@ Run `detect.py` with `webcam=True` to show a live webcam feed. **PyTorch** format: - https://drive.google.com/drive/folders/1uxgUBemJVw9wZsdpboYbzUN4bcRhsuAI -# Validation mAP +# mAP -Run `test.py` to validate the official YOLOv3 weights `weights/yolov3.weights` against the 5000 validation images. You should obtain a .584 mAP at `--img-size 416`, or .586 at `--img-size 608` using this repo, compared to .579 at 608 x 608 reported in darknet (https://arxiv.org/abs/1804.02767). +Run `test.py --save-json --conf-thres 0.005` to test the official YOLOv3 weights `weights/yolov3.weights` against the 5000 validation images. Compare to .579 at 608 x 608 reported in darknet (https://arxiv.org/abs/1804.02767). -Run `test.py --weights weights/latest.pt` to validate against the latest training results. **Default training settings produce a 0.522 mAP at epoch 62.** Hyperparameter settings and loss equation changes affect these results significantly, and additional trade studies may be needed to further improve this. +Run `test.py --weights weights/latest.pt` to validate against the latest training results. Hyperparameter settings and loss equation changes affect these results significantly, and additional trade studies may be needed to further improve this. + +``` bash +sudo rm -rf yolov3 && git clone https://github.com/ultralytics/yolov3 +# bash yolov3/data/get_coco_dataset.sh +sudo rm -rf cocoapi && git clone https://github.com/cocodataset/cocoapi && cd cocoapi/PythonAPI && make && cd ../.. && cp -r cocoapi/PythonAPI/pycocotools yolov3 +cd yolov3 && python3 test.py --save-json --conf-thres 0.005 + +... + +Namespace(batch_size=32, cfg='cfg/yolov3.cfg', conf_thres=0.005, data_cfg='cfg/coco.data', img_size=416, iou_thres=0.5, nms_thres=0.45, save_json=True, weights='weights/yolov3.weights') + +loading annotations into memory... +Done (t=4.17s) +creating index... +index created! +Loading and preparing results... +DONE (t=1.75s) +creating index... +index created! +Running per image evaluation... +Evaluate annotation type *bbox* +DONE (t=39.30s). +Accumulating evaluation results... +DONE (t=4.63s). + Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.307 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.545 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.309 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.140 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.333 + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.453 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.266 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.396 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.415 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.222 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.449 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.575 +``` # Contact