mmdetection | OpenMMLab Detection Toolbox and Benchmark | Computer Vision library

model = dict(
    type='MaskRCNN',  # The name of detector
    backbone=dict(  # The config of backbone
        type='ResNet',  # The type of the backbone, refer to https://github.com/open-mmlab/mmdetection/blob/master/mmdet/models/backbones/resnet.p  

model = dict(
    type='MaskRCNN',  # 检测器(detector)名称
    backbone=dict(  # 主干网络的配置文件
        type='ResNet',  # 主干网络的类别，可用选项请参考 https://github.com/open-mmlab/mmdetection/blob/master/mmdet/models/backbones/resnet.py#L308
        depth=50,  # 主干网络的深度，对  

{
    "images": [image],
    "annotations": [annotation],
    "categories": [category]
}


image = {
    "id": int,
    "width": int,
    "height": int,
    "file_name": str,
}

annotation = {
    "id": int,
    "image_id": int,
    "category_id": in  

# Copyright (c) OpenMMLab. All rights reserved.
import argparse
import os
import os.path as osp

import matplotlib.patches as mpatches
import matplotlib.pyplot as plt
import mmcv
import numpy as np

try:
    import imageio
except ImportError:
    ima  

# Copyright (c) OpenMMLab. All rights reserved.
import argparse

import cv2
import mmcv
import numpy as np
import torch
from torchvision.transforms import functional as F

from mmdet.apis import init_detector
from mmdet.datasets.pipelines import Comp  

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