OpenCV 对象跟踪输入格式

Question

我正在使用高速相机拍摄的每个样本（+- 100 个样本）大约 5000 张图像。

将它们全部转换为视频文件需要相当长的时间。

我的问题是：是否可以将对象跟踪应用于已排序的图像数组？

我的理解是 OpenCV 跟踪算法从提供的视频文件中提取每一帧，跟踪请求的对象并将结果与​​前一帧进行比较以确定它是否确实是同一个对象。

短版：是否可以向 OpenCV 跟踪算法提供帧而不是视频文件？

Answer 1

只需稍作修改，您就可以修改 Object Tracking using OpenCV 以处理一系列图像。

以下代码对文件夹中的图像序列进行跟踪（视频相关代码已注释）：

import cv2
import cv2
import os
import glob
import sys

# https://www.quora.com/How-can-I-read-multiple-images-in-Python-presented-in-a-folder
img_dir = "C:/Images"  # Enter Directory of all images 
data_path = os.path.join(img_dir, "*.tif") #Assume images are in tiff format
img_files = glob.glob(data_path)

# Display image for testing:
##############################
#for f1 in img_files:
#    img = cv2.imread(f1)
#    cv2.imshow('img', img)
#    cv2.waitKey(1000)

#cv2.destroyAllWindows()
##############################


# https://www.learnopencv.com/object-tracking-using-opencv-cpp-python/

(major_ver, minor_ver, subminor_ver) = (cv2.__version__).split('.')

# Set up tracker.
# Instead of MIL, you can also use

tracker_types = ['BOOSTING', 'MIL','KCF', 'TLD', 'MEDIANFLOW', 'GOTURN', 'MOSSE', 'CSRT']
tracker_type = tracker_types[2]

if int(minor_ver) < 3:
    tracker = cv2.Tracker_create(tracker_type)
else:
    if tracker_type == 'BOOSTING':
        tracker = cv2.TrackerBoosting_create()
    if tracker_type == 'MIL':
        tracker = cv2.TrackerMIL_create()
    if tracker_type == 'KCF':
        tracker = cv2.TrackerKCF_create()
    if tracker_type == 'TLD':
        tracker = cv2.TrackerTLD_create()
    if tracker_type == 'MEDIANFLOW':
        tracker = cv2.TrackerMedianFlow_create()
    if tracker_type == 'GOTURN':
        tracker = cv2.TrackerGOTURN_create()
    if tracker_type == 'MOSSE':
        tracker = cv2.TrackerMOSSE_create()
    if tracker_type == "CSRT":
        tracker = cv2.TrackerCSRT_create()

# Read video
#video = cv2.VideoCapture("videos/chaplin.mp4")

# Exit if video not opened.
#if not video.isOpened():
#    print "Could not open video"
#    sys.exit()

if not img_dir:
    print("Images folder is empty")
    sys.exit()

# Read first image
frame = cv2.imread(img_files[0])

if frame is None:
    print("Cannot read image file")
    sys.exit()

# Read first frame.
#ok, frame = video.read()
#if not ok:
#    print 'Cannot read video file'
#    sys.exit()

# Define an initial bounding box
bbox = (287, 23, 86, 320)

# Uncomment the line below to select a different bounding box
bbox = cv2.selectROI(frame, False)

# Initialize tracker with first frame and bounding box
ok = tracker.init(frame, bbox)

#while True:

# Iterate image files instead of reading from a video file
for f1 in img_files:
    frame = cv2.imread(f1)

    # Read a new frame
    #ok, frame = video.read()
    #if not ok:
    #    break

    # Start timer
    timer = cv2.getTickCount()

    # Update tracker
    ok, bbox = tracker.update(frame)

    # Calculate Frames per second (FPS)
    #fps = cv2.getTickFrequency() / (cv2.getTickCount() - timer);

    fps = 30 # We don't know the fps from the set of images

    # Draw bounding box
    if ok:
        # Tracking success
        p1 = (int(bbox[0]), int(bbox[1]))
        p2 = (int(bbox[0] + bbox[2]), int(bbox[1] + bbox[3]))
        cv2.rectangle(frame, p1, p2, (255,0,0), 2, 1)
    else:
        # Tracking failure
        cv2.putText(frame, "Tracking failure detected", (100,80), cv2.FONT_HERSHEY_SIMPLEX, 0.75,(0,0,255),2)

    # Display tracker type on frame
    cv2.putText(frame, tracker_type + " Tracker", (100,20), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (50,170,50),2);

    # Display FPS on frame
    cv2.putText(frame, "FPS : " + str(int(fps)), (100,50), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (50,170,50), 2);

    # Display result
    cv2.imshow("Tracking", frame)

    # Exit if ESC pressed
    k = cv2.waitKey(1) & 0xff 

    if k == 27:
        break