Theano错误深度学习python

Question

这是相当标准的openCV代码，其中的循环将使用haar级联分类器检测面部，然后有一个深度学习模型将检测面部的情绪。 该模型是从2013 kaggle数据集创建的，如果有人想尝试代码，则可以从此github帐户下载该模型。 fer2013_mini_XCEPTION.119-0.65.hdf5只需将一个models文件夹放在目录中，并将其重命名为model.h5

https://github.com/oarriaga/face_classification/tree/master/trained_models

该代码在Tensorflow上正常工作，但是当我运行程序KERAS_BACKEND=theano python haarMOD.py我收到一个错误，可能是由于BLAS库未正确链接？ 有人会如何使theano发挥作用吗？ 最终，我试图使该代码具有类似的变体，以便在仅与Theano一起使用的Flask服务器上工作。

import cv2
import sys, os
import pandas as pd
import numpy as np
from keras.models import load_model

#KERAS_BACKEND=theano python haarMOD.py

BASEPATH = os.path.dirname(os.path.abspath(__file__))
sys.path.insert(0, BASEPATH)
os.chdir(BASEPATH)
MODELPATH = './models/model.h5'


emotion_dict = {0: "Angry", 1: "Disgust", 2: "Fear", 3: "Happy", 4: "Sad", 5: "Surprise", 6: "Neutral"}

model = load_model(MODELPATH)

WHITE = [255, 255, 255]

def draw_box(Image, x, y, w, h):
    cv2.line(Image, (x, y), (x + int(w / 5), y), WHITE, 2)
    cv2.line(Image, (x + int((w / 5) * 4), y), (x + w, y), WHITE, 2)
    cv2.line(Image, (x, y), (x, y + int(h / 5)), WHITE, 2)
    cv2.line(Image, (x + w, y), (x + w, y + int(h / 5)), WHITE, 2)
    cv2.line(Image, (x, (y + int(h / 5 * 4))), (x, y + h), WHITE, 2)
    cv2.line(Image, (x, (y + h)), (x + int(w / 5), y + h), WHITE, 2)
    cv2.line(Image, (x + int((w / 5) * 4), y + h), (x + w, y + h), WHITE, 2)
    cv2.line(Image, (x + w, (y + int(h / 5 * 4))), (x + w, y + h), WHITE, 2)

haar_face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
video = cv2.VideoCapture('MovieSample.m4v')


while True:


    check, frame = video.read()


    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    faces = haar_face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5);
    for (x, y, w, h) in faces:
        gray_face = cv2.resize((gray[y:y + h, x:x + w]), (110, 110))
        draw_box(gray, x, y, w, h)
        roi_gray = gray[y:y + h, x:x + w]
        cropped_img = np.expand_dims(np.expand_dims(cv2.resize(roi_gray, (48, 48)), -1), 0)
        cv2.normalize(cropped_img, cropped_img, alpha=0, beta=1, norm_type=cv2.NORM_L2, dtype=cv2.CV_32F)
        prediction = model.predict(cropped_img)
        cv2.putText(gray, emotion_dict[int(np.argmax(prediction))], (x, y), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (WHITE), 1, cv2.LINE_AA)

    cv2.imshow("Face Detector", gray)
    cv2.waitKey(1)

    key = cv2.waitKey(1)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break


video.release()
cv2.destroyAllWindows()

任何提示都将不胜感激，我在CPU上运行基于Ubuntu 18.3和Anaconda 3.6的Linux Mint，这些步骤从机器学习精通到构建深度学习库。 我也在使用.AVI文件而不是网络摄像头，因为我的PC上没有网络摄像头。 将video = cv2.VideoCapture('MovieSample.m4v')的video = cv2.VideoCapture('MovieSample.m4v')更改为video = cv2.VideoCapture(0)以将openCV默认设置为USB摄像机。

https://machinelearningmastery.com/setup-python-environment-machine-learning-deep-learning-anaconda/

model = load_model(MODELPATH) if on CPU, do you have a BLAS library installed Theano can link against?弹出的错误是第17行model = load_model(MODELPATH) if on CPU, do you have a BLAS library installed Theano can link against? 有人可以提示如何解决那件事吗？

Answer 1

通过在C驱动器C:\\Users\\user\\.keras以引用"theano"而不是"tenserflow"我使代码可以在Windows计算机上工作

{
    "floatx": "float32",
    "epsilon": 1e-07,
    "backend": "theano",
    "image_data_format": "channels_last"
}

然后将在其他stackoverflow帖子中找到的这部分附加代码添加到我的原始.py文件中

import theano
theano.config.optimizer="None"