I have this machine learning code for recognizing hand gestures. It uses webcam to detect hand gestures. Problem is however whenever I run this code it opens up the webcam (which works for a second) and it crashes immediately with the error ""is not responding. Here is my opencv.py
import cv2
import numpy as np
from keras.models import load_model
from skimage.transform import resize, pyramid_reduce
model = load_model('model.h5')
while True:
cam_capture = cv2.VideoCapture(0)
_, image_frame = cam_capture.read()
# Select ROI
im2 = crop_image(image_frame, 300,300,300,300)
image_grayscale = cv2.cvtColor(im2, cv2.COLOR_BGR2GRAY)
image_grayscale_blurred = cv2.GaussianBlur(image_grayscale, (15,15), 0)
#resized_img = image_resize(image_grayscale_blurred, width = 28, height = 28, inter = cv2.INTER_AREA)
#resized_img = keras_process_image(image_grayscale_blurred)
resized_img = cv2.resize(image_grayscale_blurred,(28,28))
#ar = np.array(resized_img)
ar = resized_img.reshape(1,784)
pred_probab, pred_class = keras_predict(model, ar )
print(pred_class, pred_probab)
# Display cropped image
cv2.imshow("Image2",im2)
cv2.imshow("Image4",resized_img)
cv2.imshow("Image3",image_grayscale_blurred)
if cv2.waitKey(25) & 0xFF == ord('q'):
cv2.destroyAllWindows()
break
cam_capture.release()
cv2.destroyAllWindows()
I have deleted some redundant code. My main file is ROIinOpenCv.py
import cv2
import numpy as np
from keras.models import load_model
from skimage.transform import resize, pyramid_reduce
model = load_model('model.h5')
def get_square(image, square_size):
height, width = image.shape
if(height > width):
differ = height
else:
differ = width
differ += 4
mask = np.zeros((differ, differ), dtype = "uint8")
x_pos = int((differ - width) / 2)
y_pos = int((differ - height) / 2)
mask[y_pos: y_pos + height, x_pos: x_pos + width] = image[0: height, 0: width]
if differ / square_size > 1:
mask = pyramid_reduce(mask, differ / square_size)
else:
mask = cv2.resize(mask, (square_size, square_size), interpolation = cv2.INTER_AREA)
return mask
def keras_predict(model, image):
data = np.asarray( image, dtype="int32" )
pred_probab = model.predict(data)[0]
pred_class = list(pred_probab).index(max(pred_probab))
return max(pred_probab), pred_class
def keras_process_image(img):
image_x = 28
image_y = 28
#img = cv2.resize(img, (28,28), interpolation = cv2.INTER_AREA)
img = get_square(img, 28)
img = np.reshape(img, (image_x, image_y))
return img
def crop_image(image, x, y, width, height):
return image[y:y + height, x:x + width]
while True:
cam_capture = cv2.VideoCapture(0)
_, image_frame = cam_capture.read()
# Select ROI
im2 = crop_image(image_frame, 300,300,300,300)
image_grayscale = cv2.cvtColor(im2, cv2.COLOR_BGR2GRAY)
image_grayscale_blurred = cv2.GaussianBlur(image_grayscale, (15,15), 0)
#resized_img = image_resize(image_grayscale_blurred, width = 28, height = 28, inter = cv2.INTER_AREA)
#resized_img = keras_process_image(image_grayscale_blurred)
resized_img = cv2.resize(image_grayscale_blurred,(28,28))
#ar = np.array(resized_img)
ar = resized_img.reshape(1,784)
pred_probab, pred_class = keras_predict(model, ar )
print(pred_class, pred_probab)
# Display cropped image
cv2.imshow("Image2",im2)
cv2.imshow("Image4",resized_img)
cv2.imshow("Image3",image_grayscale_blurred)
if cv2.waitKey(25) & 0xFF == ord('q'):
cv2.destroyAllWindows()
break
cam_capture.release()
cv2.destroyAllWindows()
ps: I am using Ubuntu do you think by any chance it could be an error of granting permission to access the webcam ?
You are opening your camera in each iteration of the while loop
. That is causing the error. The fix is just creating your cam_capture
object outside the while loop
. Please refer below.
import cv2
import numpy as np
from keras.models import load_model
from skimage.transform import resize, pyramid_reduce
model = load_model('model.h5')
cam_capture = cv2.VideoCapture(0) # create camera object outside while-loop
while True:
_, image_frame = cam_capture.read()
# Select ROI
im2 = crop_image(image_frame, 300,300,300,300)
image_grayscale = cv2.cvtColor(im2, cv2.COLOR_BGR2GRAY)
image_grayscale_blurred = cv2.GaussianBlur(image_grayscale, (15,15), 0)
resized_img = cv2.resize(image_grayscale_blurred,(28,28))
ar = resized_img.reshape(1,784)
pred_probab, pred_class = keras_predict(model, ar )
print(pred_class, pred_probab)
# Display cropped image
cv2.imshow("Image2",im2)
cv2.imshow("Image4",resized_img)
cv2.imshow("Image3",image_grayscale_blurred)
if cv2.waitKey(25) & 0xFF == ord('q'):
cv2.destroyAllWindows()
break
cam_capture.release()
cv2.destroyAllWindows()
The technical post webpages of this site follow the CC BY-SA 4.0 protocol. If you need to reprint, please indicate the site URL or the original address.Any question please contact:yoyou2525@163.com.