Save images with spacebar
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parent
e7ff1ac0cb
commit
e21376465f
3 changed files with 74 additions and 76 deletions
1
.gitignore
vendored
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.gitignore
vendored
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@ -1,2 +1,3 @@
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venv/
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*.pyc
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saves/
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@ -5,6 +5,7 @@ import logging
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import argparse
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import numpy as np
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import time
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import datetime
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from PIL import ImageFont, ImageDraw, Image
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import os
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@ -34,17 +35,22 @@ class Result():
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return self
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def draw_detections(self):
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color = draw_colors[self.algorithm]
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cv2_im_rgb = cv2.cvtColor(self.visualisation,cv2.COLOR_BGR2RGB)
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# Pass the image to PIL
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pil_im = Image.fromarray(cv2_im_rgb)
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draw = ImageDraw.Draw(pil_im, 'RGBA')
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self.draw_detections_on(draw)
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return cv2.cvtColor(np.array(pil_im), cv2.COLOR_RGB2BGR)
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def draw_detections_on(self, draw: ImageDraw):
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'''
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Draw on a specified canvas
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'''
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color = draw_colors[self.algorithm]
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for detection in self.detections:
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self.draw_detection(draw, detection, color)
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self.visualisation = cv2.cvtColor(np.array(pil_im), cv2.COLOR_RGB2BGR)
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def draw_detection(self, draw: ImageDraw, detection: dict, color: tuple):
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width = 2
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@ -68,51 +74,8 @@ class Result():
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color = tuple(color)
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draw.rectangle((detection['startX'], detection['startY'], detection['endX'], detection['endY']), outline=color, width=width)
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# cv2.rectangle(rect_img, (0, 0),
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# (sub_img.shape[1]-int(width/2), sub_img.shape[0]-int(width/2)),
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# color, width)
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def draw_detections_cv2(self):
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color = draw_colors[self.algorithm]
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for detection in self.detections:
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self.draw_detection(detection, color)
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def draw_detection_cv2(self, detection, color=(0,0,255)):
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# First we crop the sub-rect from the image
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sub_img = self.visualisation[detection['startY']:detection['endY'], detection['startX']:detection['endX']]
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rect_img = sub_img.copy()
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width = 2
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cv2.rectangle(rect_img, (0, 0),
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(sub_img.shape[1]-int(width/2), sub_img.shape[0]-int(width/2)),
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color, width)
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# white_rect = np.ones(sub_img.shape, dtype=np.uint8) * 255
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# filter out weak detections by ensuring the `confidence` is
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# greater than the minimum confidence
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if detection['confidence'] > self.confidence_threshold:
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# draw the bounding box of the face along with the associated
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# probability
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text = "{:.2f}%".format(detection['confidence'] * 100)
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y = detection['startY'] - 10 if detection['startY'] - 10 > 10 else detection['startY'] + 10
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# cv2.rectangle(image, (startX, startY), (endX, endY),
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# color, 2)
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cv2.putText(self.visualisation, text, (detection['startX'], y),
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cv2.FONT_HERSHEY_SIMPLEX, 0.45, color, 2, lineType = cv2.LINE_AA)
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alpha = 1
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else:
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# At least 10% opacity
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alpha = max(.3, detection['confidence'])
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res = cv2.addWeighted(sub_img, 1-alpha, rect_img, alpha, 1.0)
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# Putting the image back to its position
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self.visualisation[detection['startY']:detection['endY'], detection['startX']:detection['endX']] = res
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def resize(self, width, height):
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# TODO resize to new target incl all detections
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img = self.visualisation
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@ -437,16 +400,22 @@ def process3_haar(in_q, out_q, cascade_file):
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# print(img)
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out_q.put(result)
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def display(image_res, q1, q2, q3, q4, fullscreen = False):
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prev_image1 = np.zeros((image_res[1],image_res[0],3), np.uint8)
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prev_image2 = np.zeros((image_res[1],image_res[0],3), np.uint8)
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prev_image3 = np.zeros((image_res[1],image_res[0],3), np.uint8)
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prev_image4 = np.zeros((image_res[1],image_res[0],3), np.uint8)
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def display(image_res, q1, q2, q3, q4, fullscreen, output_dir):
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logger = logging.getLogger('display')
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empty_image = np.zeros((image_res[1],image_res[0],3), np.uint8)
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prev_image1 = None
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prev_result2 = None
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prev_result3 = None
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prev_result4 = None
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if fullscreen:
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cv2.namedWindow("output", cv2.WND_PROP_FULLSCREEN)
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cv2.setWindowProperty("output",cv2.WND_PROP_FULLSCREEN,cv2.WINDOW_FULLSCREEN)
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override_image = None
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override_until = None
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while True:
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logging.debug('r')
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try:
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@ -454,34 +423,36 @@ def display(image_res, q1, q2, q3, q4, fullscreen = False):
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image1 = cv2.resize(image1, (image_res[0], image_res[1]))
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prev_image1 = image1
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except Empty as e:
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image1 = prev_image1
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image1 = prev_image1 if prev_image1 is not None else empty_image
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try:
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result2 = q2.get_nowait()
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result2 = result2.resize(image_res[0], image_res[1])
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result2.draw_detections()
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image2 = result2.visualisation
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# image2 = cv2.resize(image2, (image_res[0], image_res[1]))
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prev_image2 = image2
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prev_result2 = result2
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except Empty as e:
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image2 = prev_image2
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result2 = prev_result2
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finally:
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image2 = result2.draw_detections() if result2 is not None else empty_image
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try:
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result3 = q3.get_nowait()
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result3 = result3.resize(image_res[0], image_res[1])
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result3.draw_detections()
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image3 = result3.visualisation
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# image3 = cv2.resize(image3, (image_res[0], image_res[1]))
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prev_image3 = image3
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prev_result3 = result3
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except Empty as e:
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image3 = prev_image3
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result3 = prev_result3
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finally:
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image3 = result3.draw_detections() if result3 is not None else empty_image
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try:
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result4 = q4.get_nowait()
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result4 = result4.resize(image_res[0], image_res[1])
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result4.draw_detections()
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image4 = result4.visualisation
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# image4 = cv2.resize(image4, (image_res[0], image_res[1]))
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prev_image4 = image4
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prev_result4 = result4
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except Empty as e:
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image4 = prev_image4
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result4 = prev_result4
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finally:
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image4 = result4.draw_detections() if result4 is not None else empty_image
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if override_image is not None and override_until > time.time():
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cv2.imshow("output", override_image)
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else:
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override_image = None
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img_concate_Verti1 = np.concatenate((image1,image2),axis=0)
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img_concate_Verti2 = np.concatenate((image3,image4),axis=0)
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@ -493,14 +464,38 @@ def display(image_res, q1, q2, q3, q4, fullscreen = False):
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if key == ord('q'):
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break
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if key == ord(' '):
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# TODO save frame
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pass
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# TODO wait for frame to be processed. Eg. if I move and make a pic, it should use the last frame...
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output_res = (image_res[0] *2, image_res[1] * 2)
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pil_im = Image.fromarray(cv2.cvtColor(image1, cv2.COLOR_BGR2RGB))
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pil_im = pil_im.resize(output_res)
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draw = ImageDraw.Draw(pil_im, 'RGBA')
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def main(camera_id, rotate, fullscreen, cascade_file):
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if result2 is not None:
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result2.resize(output_res[0], output_res[1]).draw_detections_on(draw)
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if result3 is not None:
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result3.resize(output_res[0], output_res[1]).draw_detections_on(draw)
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if result4 is not None:
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result4.resize(output_res[0], output_res[1]).draw_detections_on(draw)
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override_image = cv2.cvtColor(np.array(pil_im), cv2.COLOR_RGB2BGR)
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override_until = time.time() + 5
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logger.info("Show frame until %f", override_until)
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# save images:
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name = datetime.datetime.now().isoformat(timespec='seconds')
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cv2.imwrite(os.path.join(output_dir, f'{name}.png'),override_image)
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cv2.imwrite(os.path.join(output_dir, f'{name}-hog.png'),result2.visualisation)
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cv2.imwrite(os.path.join(output_dir, f'{name}-dnn.png'),result3.visualisation)
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cv2.imwrite(os.path.join(output_dir, f'{name}-haar.png'),result4.visualisation)
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def main(camera_id, rotate, fullscreen, cascade_file, output_dir):
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image_size = (int(1920/2), int(1080/2))
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if not os.path.exists(cascade_file):
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raise RuntimeError(f"Cannot load OpenCV haar-cascade file '{cascade_file}'")
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if not os.path.isdir(output_dir):
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raise RuntimeError(f"Non-existent directory to store files '{output_dir}'")
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is_rotated_90 = rotate in [cv2.ROTATE_90_CLOCKWISE, cv2.ROTATE_90_COUNTERCLOCKWISE]
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@ -519,7 +514,7 @@ def main(camera_id, rotate, fullscreen, cascade_file):
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q_process3 = Queue(maxsize=1)
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p1 = Process(target=record, args=(camera_id, q_webcam1, q_webcam2,q_webcam3,q_webcam4, image_size, rotate))
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p2 = Process(target=display, args=(image_size, q_webcam1, q_process1, q_process2, q_process3, fullscreen ))
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p2 = Process(target=display, args=(image_size, q_webcam1, q_process1, q_process2, q_process3, fullscreen, output_dir ))
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p3 = Process(target=process1_hog, args=(q_webcam2, q_process1,))
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p4 = Process(target=process2_dnn, args=(q_webcam3, q_process2,))
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p5 = Process(target=process3_haar, args=(q_webcam4, q_process3,cascade_file))
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@ -15,6 +15,8 @@ if __name__ == '__main__':
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help='Rotate counter clockwise')
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parser.add_argument('--cascade', default='haarcascade_frontalface_alt2.xml',
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help='Cascade XML file to use (opencv format)')
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parser.add_argument('--output', default='saves',
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help='Directory to store images (after pressing spacebar)')
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args = parser.parse_args()
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if args.counter_clockwise:
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rotate = cv2.ROTATE_90_COUNTERCLOCKWISE
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face_recognition.comparison.main(args.camera, rotate, args.fullscreen, args.cascade)
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face_recognition.comparison.main(args.camera, rotate, args.fullscreen, args.cascade, args.output)
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