- refactored into utils.py
- added ocv_template_matching.py for evaluationof template matcher - fixed template matching from tracker bounding box
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+22
-77
@@ -1,75 +1,12 @@
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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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from template_matcher import template_match_rotation
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from util import bbox_extend, bbox_round, process_image_bbox, image_crop, bbox_add_position, to_rect
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IMG_SCALE_UP = 1
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TEMPLATE_MATCH_OVERLAP = 0.0
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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_round(src):
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x = int(round(src[0]))
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y = int(round(src[1]))
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w = int(round(src[2]))
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h = int(round(src[3]))
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return x, y, w, h
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def bbox_extend(bbox: cv2.typing.Rect, factor: float = 0):
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we2 = bbox[2]*factor/2
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he2 = bbox[3]*factor/2
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return bbox_round((bbox[0]-we2, bbox[1]-he2, bbox[2]+2*we2, bbox[3]+2*he2))
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def image_crop(src, bbox: cv2.typing.Rect):
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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 template_match_rotation(source, template, angle, center, rot_min=-1.0, rot_max=+1.0, n_steps=10, scale=1):
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best_angle = 0
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best_r = 0
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best_max_loc = 0
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r = 0
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im_source = im.resize(source, scale * source.shape[0], scale * source.shape[1])
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for dangle in np.linspace(rot_min, rot_max, n_steps):
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# rotated and scale up to IMG_SCALE_UP-size
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im_template = im.rotate(template, angle + dangle, center=center, scale=scale)
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# Perform template match operations
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res = cv2.matchTemplate(im_source, im_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_max_loc = (maxLoc[0]/scale, maxLoc[1]/scale)
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else:
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break
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angle += best_angle
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loc_x = best_max_loc[0]
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loc_y = best_max_loc[1]
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return angle, (loc_x, loc_y)
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TEMPLATE_MATCH_OVERLAP = 1.0
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def match(source, template, angle, center):
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@@ -138,8 +75,7 @@ if not ok:
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print('Cannot read video file')
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sys.exit()
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bbox_init = cv2.selectROI("Frame", frame_init, False)
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bbox_template = bbox_extend(bbox_init, TEMPLATE_MATCH_OVERLAP)
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bbox_template = cv2.selectROI("Frame", frame_init, False)
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image_template = process_image_bbox(image_crop(frame_init, bbox_template))
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ref = Reference(image_template)
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ref_center = ref.set()
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@@ -147,7 +83,7 @@ ref_center = ref.set()
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print(f"ref_center = {ref_center}")
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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_init, bbox_init)
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tracker.init(frame_init, bbox_template)
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current_angle = 0
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path = []
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@@ -166,10 +102,10 @@ while True:
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ok, bbox_tracker = tracker.update(frame)
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image_template_rotated = image_template
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bbox = bbox_round(bbox_tracker)
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bbox_tracker_ext = bbox_extend(bbox_tracker, TEMPLATE_MATCH_OVERLAP)
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if ok:
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image_bbox = process_image_bbox(image_crop(frame, bbox))
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image_bbox = process_image_bbox(image_crop(frame, bbox_tracker_ext))
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current_angle, max_loc = match(image_bbox, image_template, current_angle, ref_center)
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# determine the starting and ending (x, y)-coordinates of the
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@@ -178,16 +114,25 @@ while True:
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print(f"current_angle: {current_angle:.2f}, startX: {startX}, startY: {startY}")
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image_template_rotated = im.rotate(image_template, current_angle, center=ref_center)
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# draw the bounding box on the image
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p1 = (int(startX + bbox[0]), int(startY + 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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# Matcher
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matcher_bbox = (max_loc[0], max_loc[1], image_template.shape[1], image_template.shape[0])
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matcher_bbox_global = bbox_round(bbox_add_position(matcher_bbox, bbox_tracker))
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matcher_top_left, matcher_bottom_right = to_rect(matcher_bbox_global)
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cv2.rectangle(frame, matcher_top_left, matcher_bottom_right, (255, 0, 0), 3)
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# Tracker
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tracker_top_left, tracker_bottom_right = to_rect(bbox_round(bbox_tracker))
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cv2.rectangle(frame, tracker_top_left, tracker_bottom_right, (0, 0, 255), 3)
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# Tracker ext
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tracker_top_left, tracker_bottom_right = to_rect(bbox_round(bbox_tracker_ext))
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cv2.rectangle(frame, tracker_top_left, tracker_bottom_right, (255, 0, 255), 3)
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# Calculate Frames per second (FPS)
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fps = cv2.getTickFrequency() / (cv2.getTickCount() - timer)
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# Draw path
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line_to = (round(startX + bbox[0]), round(startY + bbox[1]))
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line_to = (round(startX + bbox_tracker[0]), round(startY + bbox_tracker[1]))
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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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