QuickYOLO:以Larq的QuickNet为骨干的二进制权重二进制输入YOLOv2实现
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2021-03-29
13:46:30
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QuickYOLO-main.zip （68个子文件） 
QuickYOLO-main 
detection_demo.py 944B .gitignore 101B object_tracker.py 6KB dataset_preparation dataset_preparation.sh 377B migrate_data.py 1KB flatten_voc.py 536B model_data mars-small128.pb 10.72MB coco 
val2017.txt 847KB coco.names 625B train2017.txt 19.62MB requirements.txt 156B detect_mnist.py 1KB deep_sort preprocessing.py 2KB nn_matching.py 6KB detection.py 2KB linear_assignment.py 8KB generate_detections.py 8KB kalman_filter.py 8KB
test_tracking.gif 22.64MB track.py 5KB iou_matching.py 3KB tracker.py 5KB LICENSE 1KB tools Convert_to_pb.py 1KB oid_to_pascal_voc_xml.py 7KB Convert_to_TRT.py 2KB XML_to_YOLOv3.py 3KB Detection_to_XML.py 3KB checkpoints checkpoint 93B README.md 3KB YOLOv3_colab_training.ipynb 1.44MB evaluate_mAP.py 12KB IMAGES 
test.mp4 7.02MB
street.jpg 454KB
tensorboard.png 102KB mnist_test.jpg 27KB city.jpg 3.86MB tracking_results.gif 22.64MB street_pred.jpg 272KB kite_pred.jpg 409KB city_pred.jpg 2.02MB kite.jpg 1.35MB demo_application Makefile 7KB install_lce.sh 730B detection.cc 8KB demo_lce.py 5KB install_opencv4.sh 1KB model.tflite 5.64MB labelmap.txt 134B export_larq_model.py 3KB Collect_training_data.py 5KB yolov3 __ init __.py 2B postprocessing.py 4KB yolov3.py 16KB yolov4.py 32KB utils.py 22KB __pycache__ dataset.cpython-36.pyc 8KB utils.cpython-36.pyc 9KB yolov3.cpython-36.pyc 8KB configs.cpython-36.pyc 1KB dataset.py 12KB configs.py 4KB mnist show_image.py 977B mnist.names 20B make_data.py 4KB mnist 
test.zip 3.67MB train.zip 20.27MB train.py 9KB资源评论
