[SlowFast代码复现] 并用自己的视频进行检测
Linux下SlowFast环境安装与运行
一、准备
1.1 SlowFast代码
官网地址：
https://github.com/facebookresearch/SlowFast
1.2 SlowFast环境准备
很多教程都说按照官方的 Installation来，本人尝试了很多次，很多包压根就装不上，如果有相同经历的朋友可以跟着我的步骤来，亲身经历且有效。
1.2.1 创建虚拟环境
conda create -n SlowFast python=3.8
以下模块的安装均采用离线方式，git到本机然后传到服务器，再进行安装。
1.2.2 安装Pytorch
conda install pytorch==1.8.0 torchvision==0.9.0 torchaudio==0.8.0 cudatoolkit=11.1 -c pytorch -c conda-forge
1.2.3 安装cocoapi
（1）下载源码：https://github.com/philferriere/cocoapi
（2）编译源码： sudo /home/wzhou/anaconda3/envs/SlowFast/bin/python setup.py install
1.2.4 安装fvcore
（1）下载源码：https://github.com/facebookresearch/fvcore
（2）编译源码：python setup.py build --force develop
1.2.5 安装detectron2
是所有模块中安装最麻烦的一步
（1）下载源码：https://github.com/facebookresearch/detectron2
（2）将下载的包detectron2复制一份到site-packages下：
cp -r detectron2/ /home/wzhou/anaconda3/envs/SlowFast/lib/python3.8/site-packages
（3）修改以下内容（共6处）参考链接
第一处：修改detectron2的setup.py中最末尾的部分
第二处：修改site-packages\torch\utils\cpp_extension.py
（site-packages所在路径：/home/wzhou/anaconda3/envs/SlowFast/lib/python3.8/site-packages）
第三处：修改site-packages\torch\include\torch\csrc\jit\runtime\argumenta_spec.h
第四处：detectron2文件夹下：\detectron2\layers\csrc\ROIAlignRotated\ROIAlignRotated_cuda.cu，将所有的ceil改为ceilf
第五处：detectron2文件夹下：\detectron2\detectron2\layers\csrc\deformable\deform_conv_cuda_kernel.cu，将所有的floor改为floorf
第六处：将detectron2\layers\csrc\deformable下三个文件的AT_CHEK全换成TORCH_CHECK
（4）编译源码: sudo /home/wzhou/anaconda3/envs/SlowFast/bin/python setup.py install
1.2.6 安装slowfast
（1）下载源码：https://github.com/facebookresearch/SlowFast
(2) 修改文件: 将setup.py里的PIL改为pillow
（3）编译源码： sudo /home/wzhou/anaconda3/envs/SlowFast/bin/python setup.py install
1.2.7 安装 pythorchvideo
（1）下载源码：https://github.com/facebookresearch/pytorchvideo
（2）编译源码：pip install -e .
二、运行测试
2.1 制作label
建一个json文件，我命名为ava.json，保存至目录：demo\AVA\ava.json， 内容如下:
{"bend/bow (at the waist)": 0, "crawl": 1, "crouch/kneel": 2, "dance": 3,
"fall down": 4, "get up": 5, "jump/leap": 6, "lie/sleep": 7, "martial art": 8,
"run/jog": 9, "sit": 10, "stand": 11, "swim": 12, "walk": 13, "answer phone": 14,
"brush teeth": 15, "carry/hold (an object)": 16, "catch (an object)": 17, "chop": 18,
"climb (e.g., a mountain)": 19, "clink glass": 20, "close (e.g., a door, a box)": 21,
"cook": 22, "cut": 23, "dig": 24, "dress/put on clothing": 25, "drink": 26,
"drive (e.g., a car, a truck)": 27, "eat": 28, "enter": 29, "exit": 30, "extract": 31,
"fishing": 32, "hit (an object)": 33, "kick (an object)": 34, "lift/pick up": 35,
"listen (e.g., to music)": 36, "open (e.g., a window, a car door)": 37,
"paint": 38, "play board game": 39, "play musical instrument": 40,
"play with pets": 41, "point to (an object)": 42, "press": 43,
"pull (an object)": 44, "push (an object)": 45, "put down": 46,
"read": 47, "ride (e.g., a bike, a car, a horse)": 48, "row boat": 49,
"sail boat": 50, "shoot": 51, "shovel": 52, "smoke": 53, "stir": 54,
"take a photo": 55, "text on/look at a cellphone": 56, "throw": 57,
"touch (an object)": 58, "turn (e.g., a screwdriver)": 59, "watch (e.g., TV)": 60,
"work on a computer": 61, "write": 62, "fight/hit (a person)": 63,
"give/serve (an object) to (a person)": 64, "grab (a person)": 65,
"hand clap": 66, "hand shake": 67, "hand wave": 68, "hug (a person)": 69,
"kick (a person)": 70, "kiss (a person)": 71, "lift (a person)": 72,
"listen to (a person)": 73, "play with kids": 74, "push (another person)": 75,
"sing to (e.g., self, a person, a group)": 76, "take (an object) from (a person)": 77,
"talk to (e.g., self, a person, a group)": 78, "watch (a person)": 79}
2.2 更改配置文件
修改SlowFast/demo/AVA/SLOWFAST_32x2_R101_50_50.yaml
TRAIN: ENABLE: False DATASET: ava BATCH_SIZE: 16 EVAL_PERIOD: 1 CHECKPOINT_PERIOD: 1 AUTO_RESUME: True CHECKPOINT_FILE_PATH: '/home/wzhou/way/llwang/SFast/configs/AVA/c2/SLOWFAST_32x2_R101_50_50.pkl' #path to pretrain model CHECKPOINT_TYPE: pytorch DATA: NUM_FRAMES: 32 SAMPLING_RATE: 2 TRAIN_JITTER_SCALES: [256, 320] TRAIN_CROP_SIZE: 224 TEST_CROP_SIZE: 256 INPUT_CHANNEL_NUM: [3, 3] DETECTION: ENABLE: True ALIGNED: False AVA: BGR: False DETECTION_SCORE_THRESH: 0.8 TEST_PREDICT_BOX_LISTS: ["person_box_67091280_iou90/ava_detection_val_boxes_and_labels.csv"] SLOWFAST: ALPHA: 4 BETA_INV: 8 FUSION_CONV_CHANNEL_RATIO: 2 FUSION_KERNEL_SZ: 5 RESNET: ZERO_INIT_FINAL_BN: True WIDTH_PER_GROUP: 64 NUM_GROUPS: 1 DEPTH: 101 TRANS_FUNC: bottleneck_transform STRIDE_1X1: False NUM_BLOCK_TEMP_KERNEL: [[3, 3], [4, 4], [6, 6], [3, 3]] SPATIAL_DILATIONS: [[1, 1], [1, 1], [1, 1], [2, 2]] SPATIAL_STRIDES: [[1, 1], [2, 2], [2, 2], [1, 1]] NONLOCAL: LOCATION: [[[], []], [[], []], [[6, 13, 20], []], [[], []]] GROUP: [[1, 1], [1, 1], [1, 1], [1, 1]] INSTANTIATION: dot_product POOL: [[[2, 2, 2], [2, 2, 2]], [[2, 2, 2], [2, 2, 2]], [[2, 2, 2], [2, 2, 2]], [[2, 2, 2], [2, 2, 2]]] BN: USE_PRECISE_STATS: False NUM_BATCHES_PRECISE: 200 SOLVER: MOMENTUM: 0.9 WEIGHT_DECAY: 1e-7 OPTIMIZING_METHOD: sgd MODEL: NUM_CLASSES: 80 ARCH: slowfast MODEL_NAME: SlowFast LOSS_FUNC: bce DROPOUT_RATE: 0.5 HEAD_ACT: sigmoid TEST: ENABLE: False DATASET: ava BATCH_SIZE: 8 DATA_LOADER: NUM_WORKERS: 2 PIN_MEMORY: True NUM_GPUS: 1 NUM_SHARDS: 1 RNG_SEED: 0 #OUTPUT_DIR: . #TENSORBOARD: # MODEL_VIS: # TOPK: 2 DEMO: ENABLE: True LABEL_FILE_PATH: "/home/wzhou/way/llwang/SFast/demo/AVA/ava.json" INPUT_VIDEO: "/home/wzhou/way/llwang/SFast/Vinput/fight_006.mp4" OUTPUT_FILE: "/home/wzhou/way/llwang/SFast/Voutput/fight_006.mp4" DETECTRON2_CFG: "COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml" DETECTRON2_WEIGHTS: detectron2://COCO-Detection/faster_rcnn_R_50_FPN_3x/137849458/model_final_280758.pkl
注意：这两个文件是我自己建的
2.3 下载权重模型
下载模型SLOWFAST_32x2_R101_50_50 .pkl 到SlowFast/configs/AVA/c2目录下，下载页面
2.4 运行检测
cd SlowFast
python tools/run_net.py --cfg demo/AVA/SLOWFAST_32x2_R101_50_50.yaml
三、错误总结
项目运行出来后，感觉也没有那么难搞了，但也确实花费我挺长时间的，就把我遇到的一些问题记录下来，其中不乏有python版本不匹配，以及下载的模块不是官方给定的，导致文件的缺失等等，也方便以后复盘。
3.1 error1
解决： 注释掉（没有任何依据，非常害怕后续的操作报错）
后续貌似并没有出现什么问题。
3.2 error2
解决：参考博客
3.3 error3
解决：注释掉这4个地方
3.4 error4
解决：原因是下载的detectron2不是官方的，导致model_zoo.py里的函数不全有缺失，重新下载官方提供的detectron2模块即可。
四、参考链接
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