问题
I'm trying to use EAST text detector to detect areas of text in images, but am having trouble on loading the pre-trained EAST text detector.
The following is my text_detection.py file
from imutils.object_detection import non_max_suppression
import numpy as np
import argparse
import time
import cv2
import requests
import urllib
# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", type=str,help="path to input image")
ap.add_argument("-east", "--east", type=str,help="path to input EAST text detector")
ap.add_argument("-c", "--min-confidence", type=float, default=0.5,help="minimum probability required to inspect a region")
ap.add_argument("-w", "--width", type=int, default=320,help="resized image width (should be multiple of 32)")
ap.add_argument("-e", "--height", type=int, default=320,help="resized image height (should be multiple of 32)")
args = vars(ap.parse_args())
# load the input image and grab the image dimensions
req = urllib.request.urlopen('https://hips.hearstapps.com/ghk.h-cdn.co/assets/18/02/mandy-hale-inspirational-quote.jpg')
arr = np.asarray(bytearray(req.read()), dtype=np.uint8)
image = cv2.imdecode(arr, -1)
orig = image.copy()
(H, W) = image.shape[:2]
# set the new width and height and then determine the ratio in change
# for both the width and height
(newW, newH) = (args["width"], args["height"])
rW = W / float(newW)
rH = H / float(newH)
# resize the image and grab the new image dimensions
image = cv2.resize(image, (newW, newH))
(H, W) = image.shape[:2]
# define the two output layer names for the EAST detector model that
# we are interested -- the first is the output probabilities and the
# second can be used to derive the bounding box coordinates of text
layerNames = [
"feature_fusion/Conv_7/Sigmoid",
"feature_fusion/concat_3"]
# load the pre-trained EAST text detector
print("[INFO] loading EAST text detector...")
net = cv2.dnn.readNet(args["east"])
# construct a blob from the image and then perform a forward pass of
# the model to obtain the two output layer sets
blob = cv2.dnn.blobFromImage(image, 1.0, (W, H),
(123.68, 116.78, 103.94), swapRB=True, crop=False)
start = time.time()
net.setInput(blob)
(scores, geometry) = net.forward(layerNames)
end = time.time()
# show timing information on text prediction
print("[INFO] text detection took {:.6f} seconds".format(end - start))
# grab the number of rows and columns from the scores volume, then
# initialize our set of bounding box rectangles and corresponding
# confidence scores
(numRows, numCols) = scores.shape[2:4]
rects = []
confidences = []
# loop over the number of rows
for y in range(0, numRows):
# extract the scores (probabilities), followed by the geometrical
# data used to derive potential bounding box coordinates that
# surround text
scoresData = scores[0, 0, y]
xData0 = geometry[0, 0, y]
xData1 = geometry[0, 1, y]
xData2 = geometry[0, 2, y]
xData3 = geometry[0, 3, y]
anglesData = geometry[0, 4, y]
# loop over the number of columns
for x in range(0, numCols):
# if our score does not have sufficient probability, ignore it
if scoresData[x] < args["min_confidence"]:
continue
# compute the offset factor as our resulting feature maps will
# be 4x smaller than the input image
(offsetX, offsetY) = (x * 4.0, y * 4.0)
# extract the rotation angle for the prediction and then
# compute the sin and cosine
angle = anglesData[x]
cos = np.cos(angle)
sin = np.sin(angle)
# use the geometry volume to derive the width and height of
# the bounding box
h = xData0[x] + xData2[x]
w = xData1[x] + xData3[x]
# compute both the starting and ending (x, y)-coordinates for
# the text prediction bounding box
endX = int(offsetX + (cos * xData1[x]) + (sin * xData2[x]))
endY = int(offsetY - (sin * xData1[x]) + (cos * xData2[x]))
startX = int(endX - w)
startY = int(endY - h)
# add the bounding box coordinates and probability score to
# our respective lists
rects.append((startX, startY, endX, endY))
confidences.append(scoresData[x])
# apply non-maxima suppression to suppress weak, overlapping bounding
# boxes
boxes = non_max_suppression(np.array(rects), probs=confidences)
# loop over the bounding boxes
for (startX, startY, endX, endY) in boxes:
# scale the bounding box coordinates based on the respective
# ratios
startX = int(startX * rW)
startY = int(startY * rH)
endX = int(endX * rW)
endY = int(endY * rH)
# draw the bounding box on the image
cv2.rectangle(orig, (startX, startY), (endX, endY), (0, 255, 0), 2)
# show the output image
cv2.imshow("Text Detection", orig)
cv2.waitKey(0)
# apply non-maxima suppression to suppress weak, overlapping bounding
# boxes
boxes = non_max_suppression(np.array(rects), probs=confidences)
# loop over the bounding boxes
for (startX, startY, endX, endY) in boxes:
# scale the bounding box coordinates based on the respective
# ratios
startX = int(startX * rW)
startY = int(startY * rH)
endX = int(endX * rW)
endY = int(endY * rH)
# draw the bounding box on the image
cv2.rectangle(orig, (startX, startY), (endX, endY), (0, 255, 0), 2)
# show the output image
cv2.imshow("Text Detection", orig)
cv2.waitKey(0)
An error
net = cv2.dnn.readNet(args["east"]) cv2.error: OpenCV(3.4.3) C:\projects\opencv-python\opencv\modules\dnn\src\dnn.cpp:3443: error: (-2:Unspecified error) Cannot determine an origin framework of files: in function 'cv::dnn::experimental_dnn_34_v7::readNet'
is shown on loading the EAST text detector
I am using opencv-python 3.4.3.18. What is the cause for this error? Does it have anything to do with the Python version?
回答1:
If someone is using the compiled c++ sample program, you need to pass the arguments with the correct syntax to opencv's CommandLineParser:
./a.out --input=./path/to/image.jpg --model=frozen_east_text_detection.pb
回答2:
The issue was that I hadn't passed the arguments. To pass the arguments using PyCharm, on the 'run'menu select "edit configurations" and pass the arguments --image : The path to the input image. --east : The EAST scene text detector model file path. --min-confidence : Probability threshold to determine text. --width : Resized image width --height : Resized image height
来源：https://stackoverflow.com/questions/53442472/error-on-loading-opencv-east-text-detector-in-python