littletomatodonkey / insight-face-paddle Goto Github PK

face_recognition识别错误率很高，（摄像头cv读出bgr已转rgb_frame = frame[:, :, ::-1]）
insight-face识别率应该很高才对啊，我要如何提高识别正确率呢

大佬 请教一下这个数据集制作有没有案例啥的，求分享一个，谢谢！

首先，Blazeface的人脸检测，对于头像占比比较大的图片，效果很差，但是对于占比小的，则效果很好。如下图的汤姆汉克斯，识别的置信度只有0.25左右

但是这样的集体照，则都在0.99左右

另外，检测和识别的过程，看deepsight的Insightface项目，应该还缺少了Alignment这一步骤，所以当脸不是正对镜头时，计算获得的特征值的余弦相似度，会很差，如和下面的汤姆汉克斯图像对照，只有0.0X的相似度。但是这个不确定，因为InsightFace里用到的人脸检测模型应该是2d106det.onnx，模型本身就不相同。

而使用insightface时，两张都相似度在0.5左右。人脸识别都是用了ArcFace模型。

hi author,
i have some problem when build the index for image. After i run this:
!python insightface_paddle.py --build_index ./demo/friends/index.bin --img_dir ./demo/friends/gallery/ --label ./demo/friends/gallery/label.txt

And have this error

So i found the weird code like this, may be it caused the issue. So i changed args.rec = False but i have another issue

Hope to see your reply soon !

Training: 2021-11-02 19:58:58,427 - Load checkpoint from '/home/bbs/Datasets/kjj/insightface/recognition/arcface_paddle/MS1M_v2_arcface_MobileFaceNet_128_0.1/MobileFaceNet_128/120'.
Traceback (most recent call last):
File "tools/train.py", line 35, in
train(args)
File "/home/bbs/Datasets/kjj/insightface/recognition/arcface_paddle/dynamic/train.py", line 168, in train
backbone, classifier, optimizer, for_train=True)
File "/home/bbs/Datasets/kjj/insightface/recognition/arcface_paddle/dynamic/utils/io.py", line 229, in load
classifier.state_dict(), dist_param_state_dict)
File "/home/bbs/Datasets/kjj/insightface/recognition/arcface_paddle/dynamic/utils/io.py", line 220, in map_actual_param_name
state_dict[name] = load_state_dict[param.name]
KeyError: 'dist@fc@rank@00000'

Hello,
I am facing very low accuracy in both recognition models (ArcFace and MobileFace), no matter how i play with the input params (such as Rec_thresh), i am not getting good results at all.
what could be wrong?

执行以下命令

insightfacepaddle --det --rec --index ./demo/friends/index.bin --input ./demo/friends/query/tmp.jpg --output ./output

我想达到效果：没有在索引库中的人被识别出人脸并锚框并提示未知，在索引库中的人被识别出人脸并锚框并提示人名，请问这个能做到吗，如何做呢

我在源码中并没有看到人脸对齐，这个识别不需要人脸对齐吗？

执行这段代码报错:
import insightface
from insightface.app import FaceAnalysis
from insightface.data import get_image as ins_get_image
app = FaceAnalysis()
app.prepare(ctx_id=0, det_size=(640, 640))
报错提示:

Hi I am testing the inference with:
RTX 3090
Cuda 11.2
paddlepaddle-gpu 2.1
Cudnn 8
And the performance for BlazeFace Detection is 20ms only. Is this normal?

当index未指定时，args.index为None，直接执行os.path.isfile(args.index)会触发异常：

Traceback (most recent call last):
File "/home/mikeshi/test/face_recog_paddle/venv/bin/insightfacepaddle", line 8, in
sys.exit(main())
File "/home/mikeshi/test/face_recog_paddle/venv/lib/python3.7/site-packages/insightface_paddle/insightface_paddle.py", line 786, in main
predictor = InsightFace(args)
File "/home/mikeshi/test/face_recog_paddle/venv/lib/python3.7/site-packages/insightface_paddle/insightface_paddle.py", line 631, in init
if not (args.build_index or os.path.isfile(args.index)):
File "/usr/lib/python3.7/genericpath.py", line 30, in isfile
st = os.stat(path)
TypeError: stat: path should be string, bytes, os.PathLike or integer, not NoneType

代码如下：

`import insightface_paddle as face
import logging

logging.basicConfig(level=logging.INFO)

parser = face.parser()
args = parser.parse_args()
args.det = True
args.rec = True
args.rec_model = 'ArcFace' # 这里使用ArcFace
args.index = './demo/friends/index.bin'
args.output = './output'
input_path = './demo/friends/query/friends2.jpg'
predictor = face.InsightFace(args=args)
res = predictor.predict(input_path, print_info=True)
print(next(res))`

报错信息如下：
Traceback (most recent call last):
File "D:/PaddleRepo/insight-face-paddle/insightface_paddle_demo.py", line 18, in
print(next(res))
File "D:\PaddleRepo\insight-face-paddle\insightface_paddle.py", line 759, in predict
labels = self.rec_predictor.retrieval(np_feature)
File "D:\PaddleRepo\insight-face-paddle\insightface_paddle.py", line 555, in retrieval
feature).squeeze()
File "D:\PaddleRepo\venv\lib\site-packages\sklearn\metrics\pairwise.py", line 1179, in cosine_similarity
X, Y = check_pairwise_arrays(X, Y)
File "D:\PaddleRepo\venv\lib\site-packages\sklearn\utils\validation.py", line 72, in inner_f
return f(**kwargs)
File "D:\PaddleRepo\venv\lib\site-packages\sklearn\metrics\pairwise.py", line 161, in check_pairwise_arrays
X.shape[1], Y.shape[1]))
ValueError: Incompatible dimension for X and Y matrices: X.shape[1] == 128 while Y.shape[1] == 512

大佬好，我想使用这个库包装成api，本地开发运行是正常的，但是打进docker之后发生了一场

调用insightface_paddle 的时候发生了异常

为啥这写参数会传递到gunicorn了

`-------------------------------------------------------------------------------------

                                  PaddleFace                                     

+----------------+------------------------------------------------------------------+

| Param | Value |

+----------------+------------------------------------------------------------------+

| det_model | BlazeFace |

| rec_model | MobileFace |

| use_gpu | True |

| enable_mkldnn | False |

| cpu_threads | 1 |

| input | None |

| output | /home/nvidia/insight-face-paddle-main/output |

| det | True |

| det_thresh | 0.8 |

| rec | True |

| index | /home/nvidia/insight-face-paddle-main/demo/predixr_img/index.bin |

| cdd_num | 5 |

| rec_thresh | 0.45 |

| max_batch_size | 1 |

| build_index | None |

| img_dir | None |

| label | None |

+----------------+------------------------------------------------------------------+

                           Powered by PaddlePaddle!                              

WARNING:root:The directory of input contine directory or not supported file type, only support: {'jpg', 'tif', 'bmp', 'jpeg', 'rgb', 'png', 'tiff'}

Traceback (most recent call last):

File "pre.py", line 16, in

print(next(res))

File "/home/nvidia/insight-face-paddle-main/insightface_paddle.py", line 759, in predict

labels = self.rec_predictor.retrieval(np_feature)

File "/home/nvidia/insight-face-paddle-main/insightface_paddle.py", line 558, in retrieval

-self.cdd_num)[-self.cdd_num:]

File "<array_function internals>", line 6, in argpartition

File "/home/nvidia/.local/lib/python3.6/site-packages/numpy/core/fromnumeric.py", line 832, in argpartition

return _wrapfunc(a, 'argpartition', kth, axis=axis, kind=kind, order=order)

File "/home/nvidia/.local/lib/python3.6/site-packages/numpy/core/fromnumeric.py", line 58, in _wrapfunc

return bound(*args, **kwds)

ValueError: kth(=-2) out of bounds (3)

`
demo测试没有问题，换成自己的数据之后似乎建立索引以后那个索引会报错，请问这个问题如何解决？
另外，请问建立索引的最少图片张数（每个人）是多少？

Hi,

Video demo is not accepting video files and asking images.

在进行人脸识别的时候，使用预训练模型，如果有index.bin我看就可以直接进行人脸识别了。请问这个文件如何生成？