125 lines
3.8 KiB
Python
125 lines
3.8 KiB
Python
import cv2
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import sys
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import imutils as im
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from util import bbox_extend, bbox_round, image_crop, to_rect, bbox_add_position, bbox_center
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COLOR_TRACKER = (0, 255, 0)
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COLOR_TRACKER_EXT = (0, 255, 255)
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COLOR_MATCHER = (0, 0, 255)
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COLOR_TEMPLATE = (255, 0, 0)
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IMG_SCALE_UP = 1
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TEMPLATE_MATCH_OVERLAP = 0
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#video = cv2.VideoCapture("./data/IMG_1730.MP4")
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video = cv2.VideoCapture('./data/spindle/%04d.png')
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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, image = 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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bb_crop = bbox_extend(cv2.selectROI("Image", image, False), TEMPLATE_MATCH_OVERLAP)
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crop = image_crop(image.copy(), bb_crop)
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bb_template = cv2.selectROI("Image", crop, fromCenter=True, showCrosshair=True)
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template = cv2.cvtColor(image_crop(crop.copy(), bb_template), cv2.COLOR_BGR2GRAY)
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# Initialize tracker with first frame and bounding box
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tracker = cv2.TrackerKCF().create()
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tracker.init(image, bb_crop)
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path = []
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line_from = None
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is_startup = True
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offset_x = 0
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offset_y = 1
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while True:
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# Read a new frame
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ok, image = 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, bb_crop = tracker.update(image)
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crop = image_crop(image.copy(), bb_crop)
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crop = cv2.cvtColor(crop, cv2.COLOR_BGR2GRAY)
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crop = cv2.GaussianBlur(crop, (15, 15), 0)
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image_anno = image.copy()
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if ok:
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# Perform template match operations
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crop_scaled = im.resize(crop.copy(), IMG_SCALE_UP * crop.shape[1], IMG_SCALE_UP * crop.shape[0])
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template_scaled = im.resize(template, IMG_SCALE_UP * template.shape[0], IMG_SCALE_UP * template.shape[1])
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res = cv2.matchTemplate(crop_scaled, template_scaled, cv2.TM_CCOEFF_NORMED)
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(min_val, max_val, min_loc, max_loc) = cv2.minMaxLoc(res)
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print(f"(min_val, max_val, min_loc, max_loc): {(min_val, max_val, min_loc, max_loc)}")
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print(f"matcher_res : {res.shape}")
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print(f"crop : {crop.shape}")
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print(f"crop_scaled : {crop_scaled.shape}")
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print(f"template : {template.shape}")
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print(f"template_scaled : {template_scaled.shape}")
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matcher_start_x = max_loc[0]/IMG_SCALE_UP
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matcher_start_y = max_loc[1]/IMG_SCALE_UP
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if is_startup:
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is_startup = False
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offset_x = matcher_start_x - bb_template[0]
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offset_y = matcher_start_y - bb_template[1]
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print(f"offset : {(offset_x, offset_y)}")
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matcher_start_x -= offset_x
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matcher_start_y -= offset_y
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print(f"matcher_start : {(matcher_start_x, matcher_start_y)}")
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matcher_bbox_local = (round(matcher_start_x), round(matcher_start_y), template.shape[1], template.shape[0])
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matcher_top_left_local, matcher_bottom_right_local = to_rect(bbox_round(matcher_bbox_local))
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matcher_bbox = bbox_round(bbox_add_position(matcher_bbox_local, bb_crop))
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matcher_rect = to_rect(matcher_bbox)
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tracker_rect = to_rect(bb_crop)
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template_top_left, template_bottom_right = to_rect(bb_template)
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cv2.rectangle(crop, template_top_left, template_bottom_right, COLOR_TEMPLATE, 1)
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cv2.rectangle(crop, matcher_top_left_local, matcher_bottom_right_local, COLOR_MATCHER, 1)
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cv2.rectangle(image_anno, matcher_rect[0], matcher_rect[1], COLOR_MATCHER, 1)
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cv2.rectangle(image_anno, tracker_rect[0], tracker_rect[1], COLOR_TRACKER, 1)
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matcher_crop = image_crop(image, matcher_bbox)
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# Draw path
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line_to = bbox_center(matcher_bbox)
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if line_from is not None:
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path.append({'from': line_from, 'to': line_to})
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line_from = line_to
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for p in path:
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cv2.line(image_anno, p['from'], p['to'], (0, 0, 255), 2)
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cv2.imshow("Crop", crop)
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cv2.imshow("Image", image_anno)
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cv2.imshow("Matcher res", res)
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cv2.imshow("Matcher view", matcher_crop)
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while True:
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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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if k == 32:
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break
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if k == 27:
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break
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