Question

从github获取基于深度网络的青光眼检测代码后，我对CNN进行了训练，并且在所有100个时期中都能很好地工作。该代码应根据视网膜眼部扫描来确定患者是否患有青光眼并输出结果。但是当我运行python GUI.py运行UI部分时，出现以下错误：

Traceback (most recent call last):
  File "GUI.py", line 11, in <module>
    model = load_model('f1.h5')
  File "/usr/local/lib/python2.7/site-packages/keras/engine/saving.py", line 492, in load_wrapper
    return load_function(*args, **kwargs)
  File "/usr/local/lib/python2.7/site-packages/keras/engine/saving.py", line 583, in load_model
    with H5Dict(filepath, mode='r') as h5dict:
  File "/usr/local/lib/python2.7/site-packages/keras/utils/io_utils.py", line 191, in __init__
    self.data = h5py.File(path, mode=mode)
  File "/usr/local/lib/python2.7/site-packages/h5py/_hl/files.py", line 408, in __init__
    swmr=swmr)
  File "/usr/local/lib/python2.7/site-packages/h5py/_hl/files.py", line 173, in make_fid
    fid = h5f.open(name, flags, fapl=fapl)
  File "h5py/_objects.pyx", line 54, in h5py._objects.with_phil.wrapper
  File "h5py/_objects.pyx", line 55, in h5py._objects.with_phil.wrapper
  File "h5py/h5f.pyx", line 88, in h5py.h5f.open
IOError: Unable to open file (file signature not found)

这是我的文件目录：

这是我的代码：

from Tkinter import *
import tkMessageBox as messagebox
from keras.models import load_model
import matplotlib.pyplot as plt
import cv2
import numpy as np
import os
import pandas


model = load_model('f1.h5')


def get_filenames():
    global path
    path = r"test"
    return os.listdir(path)


def curselect(event):
    global spath
    index = t1.curselection()[0]
    spath = t1.get(index)
    return(spath)


def autoroi(img):

    gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    thresh = cv2.threshold(gray_img, 130, 255, cv2.THRESH_BINARY)[1]
    thresh = cv2.dilate(thresh, None, iterations=5)

    contours, hierarchy = cv2.findContours(
        thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

    biggest = max(contours, key=cv2.contourArea)
    x, y, w, h = cv2.boundingRect(biggest)
    cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 2)
    roi = img[y:y+h, x:x+w]

    return roi


def prediction():

    img = cv2.imread('test/%s' % (spath))
    img = autoroi(img)
    img = cv2.resize(img, (256, 256))
    img = np.reshape(img, [1, 256, 256, 3])

    prob = model.predict(img)
    Class = prob.argmax(axis=-1)

    return(Class)


def run():

    Class = prediction()
    if (Class == 0):
        messagebox.showinfo('Prediction', 'You have been diagnosed with Glaucoma')
    else:
        messagebox.showinfo('Prediction', 'Congratulations! You are Healthy')


def run_all():

    x = os.listdir(path)
    y = []
    affected = 0

    for i in x:
        img = cv2.imread('test/%s' % (i))
        img = autoroi(img)
        img = cv2.resize(img, (256, 256))
        img = np.reshape(img, [1, 256, 256, 3])

        prob = model.predict(img)
        Class = prob.argmax(axis=-1)
        y.append(Class[0])
        if Class == 1:
            affected += 1

    df = pandas.DataFrame(data=y, index=x, columns=["output"])
    df.to_csv('output.csv', sep=',')


def ROI():
    img = cv2.imread('test/%s' % (spath))
    roi = autoroi(img)
    cv2.imshow("Region of Interest", roi)


def preview():
    img = cv2.imread('test/%s' % (spath))
    cv2.imshow('Image', img)


def graph():

    total = len(os.listdir(path))
    affected = pandas.read_csv('output.csv')
    affected = affected['output'].sum()

    healthy = total - affected

    piey = ["Glaucomatous", "Healthy"]
    piex = [affected, healthy]

    plt.axis("equal")
    plt.pie(piex, labels=piey, radius=1.5, autopct='%0.1f%%', explode=[0.2, 0])
    plt.show()

# Frontend GUI


window = Tk()
window.title("Glaucoma Detection")
window.geometry('1000x550')
window.configure(background='grey')

l1 = Label(window, text="Test Image", font=("Arial", 20), padx=10, bg='grey')
l1.grid(row=0, column=0)

b1 = Button(window, text='Run', font=("Arial", 20), command=run)
b1.grid(row=1, column=3)

b2 = Button(window, text='Preview', font=("Arial", 20), command=preview)
b2.grid(row=1, column=2, rowspan=2, padx=10)

b2 = Button(window, text='ROI', font=("Arial", 20), command=ROI)
b2.grid(row=2, column=2, rowspan=3, padx=10)

b3 = Button(window, text='Run all', font=("Arial", 20), command=run_all)
b3.grid(row=2, column=3)

b4 = Button(window, text='Graph', font=("Arial", 20), command=graph)
b4.grid(row=3, column=3)

t1 = Listbox(window, height=20, width=60, selectmode=SINGLE, font=("Arial", 15), justify=CENTER)
t1.grid(row=1, column=0, rowspan=3, padx=10)
for filename in get_filenames():
    t1.insert(END, filename)
t1.bind('<<ListboxSelect>>', curselect)

sb1 = Scrollbar(window)
sb1.grid(row=1, column=1, rowspan=4)

t1.configure(yscrollcommand=sb1.set)
sb1.configure(command=t1.yview)


window.mainloop()

为什么我无法加载重量文件-“ f1.h5”？

无法加载f1.h5文件

0 个答案: