根据requirements - 开源项目默认的.txt进行库安装
环境：WIN10 + Anoconda + Pycharm + python3.6.2
mask_rcnn基本流程1、训练
1)labelme进行目标物体标记，生成json文件，含点坐标、以及各个物体的标签label;
json文件的格式：（在balloon.py中提到）
# { 'filename': '28503151_5b5b7ec140_b.jpg',# 'regions': {# '0': {# 'region_attributes': {},# 'shape_attributes': {# 'all_points_x': [...],# 'all_points_y': [...],# 'name': 'polygon'}},# ... more regions ...# },# 'size': 100202# }2)修改E:\gitHubProjects\Mask_RCNN-master\Mask_RCNN-master\samples\balloon\balloon.py代码将：
if args.weights.lower() == "coco":# Exclude the last layers because they require a matching# number of classes,coco数据集含有80个类，但是对于通常来说，只有前景和背景两类，因此#需要将if。。=coco给注释掉model.load_weights(weights_path, by_name=True, exclude=["mrcnn_class_logits", "mrcnn_bbox_fc","mrcnn_bbox", "mrcnn_mask"])else:model.load_weights(weights_path, by_name=True)
改成：
model.load_weights(weights_path, by_name=True, exclude=["mrcnn_class_logits", "mrcnn_bbox_fc","mrcnn_bbox", "mrcnn_mask"])3)利用balloon.py修改后的进行训练，注意需要修改的地方：
class BalloonConfig(Config):"""Configuration for training on the toy dataset.Derives from the base Config class and overrides some values."""# Give the configuration a recognizable nameNAME = "balloonDataset"# We use a GPU with 12GB memory, which can fit two images.# Adjust down if you use a smaller GPU.IMAGES_PER_GPU = 1 # 每个GPU同时训练的图片数，如果是CPU建议修改为1# Number of classes (including background)# 类别数，一般是你自己数据物体的类别数+1（+1是背景），coco默认的是80+1类NUM_CLASSES = 1 + 1 # Background + balloonDataset# Number of training steps per epoch # 每一个迭代循环的步长数STEPS_PER_EPOCH = 100# Skip detections with < 90% confidence 置信度，小于这个则跳过检测，提高检测效率DETECTION_MIN_CONFIDENCE = 0.9
除了上面的，还可以修改训练好的模型存放的位置，一般存放在E:\gitHubProjects\Mask_RCNN-master\Mask_RCNN-master\logs4) 利用命令行进行训练，具体命令见：见“E:\gitHubProjects\Mask_RCNN-master\Mask_RCNN-master\samples\balloon\README.md”
python3 balloon.py train --dataset=dataset_path --weights=weughts_path2、测试
1)修改E:\gitHubProjects\Mask_RCNN-master\Mask_RCNN-master\samples\coco\coco.py代码
将：
NUM_CLASSES = 1+80
改成:
NUM_CLASSES = 1+1(背景+目标)————根据自己的类别数进行修改
1)修改E:\gitHubProjects\Mask_RCNN-master\Mask_RCNN-master\samples\demo.py代码
修改MODEL_DIR、COCO_MODEL_PATH（训练好的模型）、IMAGE_DIR（测试集图片）、class_names（类别名称）=["BG","","",...]
github项目链接：
https://github.com/1371174718/Mask_RCNN_master
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