def vid_stream():
while cap.isOpened():
_, frame = cap.read()
if frame is None:
continue
cv2.imshow("drone", frame)
key = cv2.waitKey(1) & 0xFF
if key == 27:
break
cap.release()
cv2.destroyALlWindows()
drone.streamoff()
def main():
cg = CameraGyroscope()
video_data = cv2.VideoCapture(0)
while True:
_,frame2 = video_data.read()
time1 = time.time()
# time.sleep(0.1)
_,frame1 = video_data.read()
frame2 = cv2.cvtColor(frame2,cv2.COLOR_BGR2GRAY)
frame2 = np.divide(frame2,np.mean(frame2))
frame1 = cv2.cvtColor(frame1,cv2.COLOR_BGR2GRAY)
frame1 = np.divide(frame1,np.mean(frame1))
time2 = time.time()
cg.extract_angle_update(frame1,frame2,time1,time2)
cv2.imshow("frame1",frame1)
key = cv2.waitKey(1)
if key == ord('q'):
break
cv2.destroyALlWindows()
#Extract (Crop out the required face) : Region of Interest
offset = 10
face_section = frame[y - offset:y + h + offset,
x - offset:x + w + offset]
face_section = cv2.resize(face_section, (100, 100))
skip += 1
if skip % 10 == 0:
face_data.append(face_section)
print(len(face_data))
cv2.imshow("Frame", frame)
cv2.imshow("Face Section", face_section)
key_pressed = cv2.waitKey(1) & 0xFF
if key_pressed == ord('q'):
break
# Convert our face list array into a numpy array
face_data = np.asarray(face_data)
face_data = face_data.reshape((face_data.shape[0], -1))
print(face_data.shape)
# Save this data into file system
np.save(dataset_path + file_name + '.npy', face_data)
print("Data Successfully saved at " + dataset_path + file_name + '.npy')
cap.release()
cv2.destroyALlWindows()
def main(_argv):
physical_devices = tf.config.experimental.list_physical_devices('GPU')
for physical_device in physical_devices:
tf.config.experimental.set_memory_growth(physical_device, True)
# import weights
yolo = YoloV3(classes=FLAGS.num_classes)
yolo.load_weights(FLAGS.weights)
logging.info("weights loaded")
# Import classes
class_names = [c.strip() for c in open(FLAGS.classes).readlines()]
logging.info("classes loaded")
# list of time for procces on each frame
times = []
# try to load webcam or a video file
try:
vid = cv2.VideoCapture(int(FLAGS.video))
except:
vid = cv2.VideoCapture(FLAGS.video)
out = None
if FLAGS.output:
#by default VideoCapture returns float instead of int
width = int(vid.get(cv2.CAP_PROP_FRAME_WIDTH))
height = int(vid.get(cv2.CAP_PROP_FRAME_HEIGHT))
fps = int(vid.get(cv2.CAP_PROP_FPS))
codec = cv2.VideoWriter_fourcc(*FLAGS.output_format)
out = cv2.VideoWriter(FLAGS.output, codec, fps, (width, height))
while True:
_, img = vid.read()
if img is None:
logging.info("Empty Frame")
time.sleep(0.1)
img_in = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
img_in = tf.expand_dims(img_in, 0)
img_in = transform_images(img_in, FLAGS.size)
t1 = time.time()
boxes, scores, classes, nums = yolo.predict(img_in)
for i in num:
print(i)
t2 = time.time()
times.append(t2 - t1)
times = times[-20:]
img = draw_outputs(img, (boxes, scores, classes, nums), class_names)
img = cv2.putText(
img, "Time: {:.2f}ms".format(sum(times) / len(times) * 1000),
(0, 30), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (1, 0, 255), 2)
if FLAGS.output:
out.write(img)
cv2.imshow('Output', img)
if cv2.waitKey(1) == ord('q'):
break
vid.release()
cv2.destroyALlWindows()
import numpy as np
import cv2
#load a color image in grayscale
img=cv2.imread('images/fruits.jpg',0)
#display an image
cv2.imshow('image',img)
#cv2.waitKey(0)
#cv2.destroyAllWindows()
k=cv2.waitKey(0) & 0xFF
if k==27: #wait for ESC key to exit
cv2.destroyALlWindows()
elif k==ord('s'): #wait 's' key to save and exit
cv2.imwrite('images/fruits_gray.jpg',img)
cv2.destroyAllWindows()
