Failed to find TIFF library

ImportError: Failed to find TIFF library. Make sure that libtiff is installed and its location is listed in PATH|LD_LIBRARY_PATH|..

解决方法：
I have actually experienced the same problem as elktoe when I tried to install libtiff on my current Mac workstation, this can be solved perfectly with mac compiled libtiff with brew. Make sure you get rid of the previous not working libtiff module before you install mac compiled libtiff
pip3 uninstall libtiff
then
brew install libtiff as suggested by @lsqshr, see if it works.

Cannot import name relu6

Just execute these commands:

git clone https://github.com/apple/coremltools.git
cd coremltools
cmake . -DPYTHON=$(which python) -DPYTHON_CONFIG=$(which python-config)
make
pip install -e .

FPN网络训练报错PaddingFIFOQueue '_1_get_batch/batch/padding_fifo_queue' is closed and has insufficient elements (requested 1, current size 0)

https://github.com/DetectionTeamUCAS/FPN_Tensorflow
按说明设置自己的训练集后，进入tool/运行train.py后报错：

PaddingFIFOQueue '_1_get_batch/batch/padding_fifo_queue' is closed and has insufficient elements (requested 1, current size 0)

查了一下，应该是xml文件中box坐标范围导致的。修改data/io/convert_data/io/convert_to_tfrecord.py中line68为

  gtbox_label = np.array(box_list, dtype=np.int32)  # [x1, y1. x2, y2, label]

  xmin, ymin, xmax, ymax, label = gtbox_label[:, 0], gtbox_label[:, 1], gtbox_label[:, 2],\
      gtbox_label[:, 3], gtbox_label[:, 4]

  xmin = np.where(xmin <= 0, 1, xmin)
  ymin = np.where(ymin <= 0, 1, ymin)
  xmax = np.where(xmax >= img_width, img_width-1, xmax)
  ymax = np.where(ymax >= img_height, img_height-1, ymax)

  # [ymin, xmin, ymax, xmax, label]
  gtbox_label = np.transpose(np.stack([ymin, xmin, ymax, xmax, label], axis=0))

即可。

TypeError: ...has type str, but expected one of: bytes

在python3环境中将数据转为TFRecord时遇到的问题
return tf.train.Feature(bytes_list=tf.train.BytesList(value=[value]))
TypeError: 'rock' has type str, but expected one of: bytes

解决方式：

转byte feature时用tf.compat.as_bytes(value)将字节或 Unicode 转换为 bytes，使用 UTF-8 编码文本：

def _bytes_feature(value):

  value = tf.compat.as_bytes(value)#####

  return tf.train.Feature(bytes_list=tf.train.BytesList(value=[value]))

pip2与pip3共存

之前修改了导致pip2无法使用，导致一些开发工具无法使用。 可以先解除 python3的软连接, 然后再修改成 python2的. mac 自带的是 python2.7
1. 先获取2.7的路径:
which python2.7, 我的是/usr/bin/python2.7

2. 解除原有链接 unlink /usr/bin/python

3. 恢复默认链接: sudo ln -s python2 /usr/bin/python

行人重识别

项目地址：
https://github.com/huanghoujing/person-reid-triplet-loss-baseline#visualize-ranking-list
test命令：

python2 script/experiment/train.py -d '(0,)' --only_test true --dataset duke --last_conv_stride 1 --normalize_feature false --exp_dir exp --model_weight_file /home/zhoujie/person-reid-triplet-loss-baseline/model_weight/duke_stride1/model_weight.pth


项目地址：
https://github.com/layumi/Person_reID_baseline_pytorch/tree/master/tutorial
train命令：

python train.py --gpu_ids 0 --name ft_ResNet50 --train_all --batchsize 32  --data_dir /home/zhoujie/Person_reID_baseline_pytorch

coco数据集转换pascal VOC数据集

1）得到annotations/json格式：labelme2coco.py

输入： 
 # 把所有的jpg和json都放到了images目录下
    base_dir = '/Users/sisyphus/TIANCHI_XUELANG_AI_gangban/data/image'

输出：
 # 把训练集转化为COCO的json格式
    l2c_train = Lableme2CoCo()
    train_instance = l2c_train.to_coco(train_path)
    l2c_train.save_coco_json(train_instance, '/Users/sisyphus/TIANCHI_XUELANG_AI_gangban/data/annotations/instances_train2017.json')

    # 把验证集转化为COCO的json格式
    l2c_val = Lableme2CoCo()
    val_instance = l2c_val.to_coco(val_path)
    l2c_val.save_coco_json(val_instance, '/Users/sisyphus/TIANCHI_XUELANG_AI_gangban/data/annotations/instances_val2017.json')


2）得到根目录下单个json文件：getclassnum.py

输入：cocojson="/Users/sisyphus/TIANCHI_XUELANG_AI_gangban/data/annotations/instances_train2017.json"

输出：
COCO_train.json


3）得到VOC xml标注文件：createXML.py

输入：
_IMAGE_PATH = '/Users/sisyphus/TIANCHI_XUELANG_AI_gangban/data/imageonly/'

with open("COCO_train.json", "r") as f:
        ann_data = json.load(f)

输出：
_ANNOTATION_SAVE_PATH = '/Users/sisyphus/TIANCHI_XUELANG_AI_gangban/data/VOC2018/Annotations'

4）生成ImageSets/Main/text文件：darknet/traintxt.py

输入：
xmlfilepath = '/Users/sisyphus/tf-faster-rcnn/data/VOCdevkit2007/VOC2007/Annotations'

输出：
saveBasePath = "/Users/sisyphus/tf-faster-rcnn/data/VOCdevkit2007/VOC2007/"

ftrainval = open(os.path.join(saveBasePath,'ImageSets/Main/trainval.txt'), 'w') 
ftest = open(os.path.join(saveBasePath,'ImageSets/Main/test.txt'), 'w') 
ftrain = open(os.path.join(saveBasePath,'ImageSets/Main/train.txt'), 'w') 
fval = open(os.path.join(saveBasePath,'ImageSets/Main/val.txt'), 'w') 


PS：
数据增强：
/Users/sisyphus/TIANCHI_XUELANG_AI_gangban/src/DataAugForTrainAndTest_DET.py

重命名jpg或xml名称：
mAP/changeTextName.py

修改xml中对应图片名称：
py/xmlEdit2.py

tf faster rcnn推导测试集计算mAP报错

训练完毕后运行./experiments/scripts/test_faster_rcnn.sh 0 pascal_voc res101
测试mAP，报错：

and the problem:
VOC07 metric? Yes
000001
Traceback (most recent call last):
File "./tools/test_net.py", line 90, in
test_net(net, imdb, max_per_image=args.max_per_image, vis=args.vis)
File "/home/rs/myGithub/py-faster-rcnn/tools/../lib/fast_rcnn/test.py", line 295, in test_net
imdb.evaluate_detections(all_boxes, output_dir)
File "/home/rs/myGithub/py-faster-rcnn/tools/../lib/datasets/pascal_voc.py", line 322, in evaluate_detections
self._do_python_eval(output_dir)
File "/home/rs/myGithub/py-faster-rcnn/tools/../lib/datasets/pascal_voc.py", line 285, in _do_python_eval
use_07_metric=use_07_metric)
File "/home/rs/myGithub/py-faster-rcnn/tools/../lib/datasets/voc_eval.py", line 127, in voc_eval
R = [obj for obj in recs[imagename] if obj['name'] == classname]
KeyError: '000001'

解决方法：

had the same problem with an old annotation cache. Just delete it
rm data/VOCdevkit2007/annotations_cache/annots.pkl and run the program again.
You should also delete the roidb cache:
rm data/cache/voc_2007_trainval_gt_roidb.pkl

PS：如要可视化测试结果，可在CPU电脑上运行tf-faster-rcnn/tools/demo_one.py程序。

tf faster rcnn 训练自己的数据集

1 按照https://github.com/endernewton/tf-faster-rcnn中介绍步骤安装项目。

2 用自己的数据集替换VOC2007数据集文件夹。

3 修改lib/datasets/pascal_voc.py中

self._classes = ('__background__',  # always index 0       "defect0","defect1","defect2","defect3","defect4","defect5","defect6","defect7","defect8","defect9")####################
 
4 lib/datasets/factory.py和experiments/scripts/train_faster_rcnn, experiments/scripts/test_faster_rcnn中，因为自己数据集名称和VOC2007一致，暂不用修改。

5 开始训练

./experiments/scripts/train_faster_rcnn.sh 0 pascal_voc res101
注意每次训练前删除output和data/cache文件夹。

训练时其它可能需要修改的参数：
1）修改迭代次数：experiments/scripts/train_faster_rcnn.sh文件中修改迭代次数

experiments/scripts/test_faster_rcnn.sh中也相应修改
2) 学习率设置：tf-faster-rcnn/lib/model/config.py文件中设置



6 tools/demo.py修改种类数
net.create_architecture("TEST", 11,#####################21


可能出现的错误：
1）InvalidArgumentError (see above for traceback): Nan in summary histogram for: 


it's because in the file 'pascal_voc.py', the function '_load_pascal_annotation' has an operation of make pixel indexes 0-based,the code is :
x1 = float(bbox.find('xmin').text) - 1
y1 = float(bbox.find('ymin').text) - 1
x2 = float(bbox.find('xmax').text) - 1
y2 = float(bbox.find('ymax').text) - 1
删除-1

2）assert(cfg.TRAIN.BATCH_SIZE % num_images == 0), 
ZeroDivisionError: integer division or modulo by zero

test.txt不能为空

xml和json无法显示中文

解决办法：在相关语句中添加“encoding='utf-8'”。
如：

xmldoc.write(xmlpath+xmllist[i], encoding='utf-8')

json.dump(instance, open(save_path, 'w', encoding='utf-8'), ensure_ascii=False, indent=1)

with open(path, "r", encoding='utf-8') as f:

ImportError: No module named Cython.Distutils

Ubuntu下使用tensorflow版faster-RCNN执行make命令报错

For python3 use

sudo apt-get install cython3

For python2 use

sudo apt-get install cython