163 lines
4.0 KiB
Python
163 lines
4.0 KiB
Python
import cv2
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import sys
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import numpy as np
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import imutils as im
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IMG_SCALE_UP = 2
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TEMPLATE_SEARCH_AREA = 0.5
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(major_ver, minor_ver, subminor_ver) = cv2.__version__.split('.')
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print(cv2.__version__)
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def bbox_extend(bbox: cv2.typing.Rect, search_area: float):
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we2 = int(round(bbox[2]*search_area/2))
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he2 = int(round(bbox[3]*search_area/2))
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res = (int(round(bbox[0]-we2)),)
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res += (int(round(bbox[1]-he2)),)
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res += (int(bbox[2]+2*we2),)
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res += (int(bbox[3]+2*he2),)
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return res
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def image_crop(src, bbox: cv2.typing.Rect, search_area: float = 0):
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bbox = bbox_extend(bbox, search_area)
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x = bbox[0]
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y = bbox[1]
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w = bbox[2]
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h = bbox[3]
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dst = src[y:y+h, x:x+w]
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return dst
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def process_image_bbox(src):
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# convert to gray
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gray = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
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return gray
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def match(source, template, current_angle):
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best_angle = 0
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best_r = 0
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best_maxLoc = 0
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image_source = im.resize(source, IMG_SCALE_UP * source.shape[0], IMG_SCALE_UP * source.shape[1])
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for dangle in np.linspace(-1.0, +1.0, 10):
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# scale up to IMG_SCALE_UP-size
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image_template = im.resize(template, IMG_SCALE_UP * template.shape[0], IMG_SCALE_UP * template.shape[1])
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# rotated
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image_template = im.rotate(image_template, current_angle + dangle)
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# Perform template match operations
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res = cv2.matchTemplate(image_source, image_template, cv2.TM_CCOEFF_NORMED)
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(minVal, maxVal, minLoc, maxLoc) = cv2.minMaxLoc(res)
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r = maxVal
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if r > best_r:
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best_r = r
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best_angle = dangle
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best_maxLoc = maxLoc
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current_angle += best_angle
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return current_angle, best_maxLoc
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trackers = {
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'KCF': cv2.TrackerKCF,
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'CSRT': cv2.TrackerCSRT,
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'MIL': cv2.TrackerMIL,
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'GOTURN': cv2.TrackerGOTURN,
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'NANO': cv2.TrackerNano,
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'MOSSE': cv2.legacy.TrackerMOSSE,
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'TLD': cv2.legacy.TrackerTLD,
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'BOOSTING': cv2.legacy.TrackerBoosting,
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'MEDIANFLOW': cv2.legacy.TrackerMedianFlow
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}
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tracker_type = 'MOSSE'
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tracker = trackers[tracker_type].create()
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video = cv2.VideoCapture("./data/production_id 4525346 (1080p).mp4")
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# Exit if video not open
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# d.
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if not video.isOpened():
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print("Could not open video")
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sys.exit()
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# Read first frame.
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ok, frame = video.read()
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if not ok:
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print('Cannot read video file')
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sys.exit()
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# Uncomment the line below to select a different bounding box
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bbox = cv2.selectROI("Frame", frame, False)
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image_template = process_image_bbox(image_crop(frame, bbox, TEMPLATE_SEARCH_AREA))
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# Initialize tracker with first frame and bounding box
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tracker.create()
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tracker.init(frame, bbox)
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current_angle = 0
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while True:
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# Read a new frame
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ok, frame = video.read()
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if not ok:
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break
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# Start timer
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timer = cv2.getTickCount()
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# Update tracker
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ok, bbox = tracker.update(frame)
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image_bbox = process_image_bbox(image_crop(frame, bbox))
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image_template_rotated = image_template
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if ok:
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current_angle, max_loc = match(image_bbox, image_template, current_angle)
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image_template_rotated = im.rotate(image_template, current_angle)
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# determine the starting and ending (x, y)-coordinates of the
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# bounding box
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(startX, startY) = max_loc
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startX += bbox[0]
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startY += bbox[1]
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endX = startX + bbox[2]
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endY = startY + bbox[3]
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print(f"startX: {startX}, startY: {startY}")
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# draw the bounding box on the image
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p1 = (int(bbox[0]), int(bbox[1]))
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p2 = (int(bbox[0] + bbox[2]), int(bbox[1] + bbox[3]))
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cv2.rectangle(frame, p1, p2, (255, 0, 0), 3)
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# Calculate Frames per second (FPS)
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fps = cv2.getTickFrequency() / (cv2.getTickCount() - timer)
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else:
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# Tracking failure
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cv2.putText(frame, "Tracking failure detected", (100, 80), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (0, 0, 255), 2)
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# Display tracker type on frame
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cv2.putText(frame, tracker_type + " Tracker", (100, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (50, 170, 50), 2)
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# Display FPS on frame
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cv2.putText(frame, "FPS : " + str(int(fps)), (100, 50), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (50, 170, 50), 2)
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# Display result
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cv2.imshow("Tracking", frame)
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cv2.imshow("image_bbox", image_template_rotated)
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# Exit if ESC pressed
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k = cv2.waitKey(1) & 0xff
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if k == 27:
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break
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