Video_object_detection_test.py

# coding: utf-8
import json
import matplotlib.pyplot as plt
from PIL import Image, ImageDraw
import numpy as np
import cv2

# Find OpenCV version
(major_ver, minor_ver, subminor_ver) = (cv2.__version__).split('.')

def getFPS(video):
    major_version = major_ver;
    if not major_version:
        (major_version, _, _) = (cv2.__version__).split('.')
        
    if int(major_version)  < 3 :
        fps = video.get(cv2.cv.CV_CAP_PROP_FPS)
    else :
        fps = video.get(cv2.CAP_PROP_FPS)
    return fps
    

def getFrameAtTime(video, timeInSec, fps):
    frameNumber = int(timeInSec* fps);
    video.set(cv2.CAP_PROP_POS_FRAMES, frameNumber-1)
    success, frame = video.read()
    if not success:
        print ("Failed to get image from frame number " + str(frameNumber));
    return frame;

colors=[(255,0,0,120), (0,255,0,120), (0,0,255,120), (255,255,0,120), 
        (0,255,255,120), (255,0,255,120), (128,128,0,120), (155,0,155,120), (155,155,20,120)]
videoPath = '/Users/mohan/Downloads/cars5.mp4'
outpath = "/Users/mohan/Downloads/test/"
dataturks_JSON_FilePath = "/Users/mohan/Downloads/Demo_Video_Bounding_Box.json"
lines = []
with open(dataturks_JSON_FilePath, 'r') as f:
    lines = f.readlines()
    
data = json.loads(lines[0]) #just showing this for one video.

# read the video from local filesystem.
vidcap = cv2.VideoCapture(videoPath)
fps = getFPS(vidcap)

columns = 3
objNumber = 0
# for each object in the video.
for obj in data["annotation"]:
    objNumber +=1
    labelName = obj["label"]
    print("Object #" + str(objNumber) + ": " + labelName)
    boundingColor = colors[objNumber%len(colors)]
    figure=plt.figure(figsize=(15,10))
    # display all the positions of the object in the video.
    positionNumber = 0;
    for pos in obj["positions"]:
        time = pos["time"] #the time of bounding box.
        points = pos["points"]
        frame = getFrameAtTime(vidcap, time, fps); #extract the frame at the given time,\.
        
        #save the frame as an image.
        num = int(time*fps)
        outImgPath = outpath + "cars_image%d.jpg" % num
        cv2.imwrite(outImgPath, frame)
        
        #draw a bounding box on the frame image.
        im = Image.open(outImgPath)
        width, height = im.size
        draw = ImageDraw.Draw(im, 'RGBA')
        #draw the bounding box.
        draw.rectangle(((points[0][0]*width,points[0][1]*height), (points[3][0]*width,points[3][1]*height)), boundingColor)
        #display the image in columns.
        figure.add_subplot(len(obj["positions"])/columns + 1, columns, positionNumber + 1)
        plt.imshow(np.asarray(im))
        positionNumber+=1
    plt.show()