[mobiface] #python #tracking #mobiface

download_videos.py

from subprocess import call
from glob import glob
import threading
import queue

anno_files = glob('./*.csv')
vids = []
for af in anno_files:
    with open(af) as f:
        lines = f.readlines()
    lines = lines[1:]
    ids = [l.split(',')[0] for l in lines]
    vids = vids + ids

vids = set(vids)

q = queue.Queue()
def worker():
    vid = q.get()
    if vid is None:
        return
    command = "youtube-dl https://www.youtube.com/watch?v={} --id".format(vid)
    call(command.split(), shell=False)


for vid in vids:
    q.put(vid)

threads = [ threading.Thread(target=worker) for _i in range(20) ]

for thread in threads:
  thread.start()
  q.put(None)  # one EOF marker for each thread

run_tracker.py

import numpy as np
import time
from eco import ECOTracker
import cv2
import glob
import os
from tqdm import tqdm
from PIL import Image
import json


def run_ECO(seq, rp, saveimage):
    x = seq.init_rect[0]
    y = seq.init_rect[1]
    w = seq.init_rect[2]
    h = seq.init_rect[3]

    frames = [np.array(Image.open(filename)) for filename in seq.s_frames]
    # frames = [cv2.cvtColor(cv2.imread(filename), cv2.COLOR_BGR2RGB) for filename in seq.s_frames]
    if len(frames[0].shape) == 3:
        is_color = True
    else:
        is_color = False
        frames = [frame[:, :, np.newaxis] for frame in frames]
    tic = time.clock()
    # starting tracking
    tracker = ECOTracker(is_color)
    res = []
    for idx, frame in enumerate(frames):
        print(idx)
        if idx == 0:
            bbox = (x, y, w, h)
            tracker.init(frame, bbox)
            bbox = (bbox[0], bbox[1], bbox[0]+bbox[2], bbox[1]+bbox[3])
        elif idx < len(frames) - 1:
            bbox = tracker.update(frame, True)
        else: # last frame
            bbox = tracker.update(frame, False)
        res.append((bbox[0], bbox[1], bbox[2]-bbox[0], bbox[3]-bbox[1]))
    duration = time.clock() - tic
    result = {}
    result['res'] = res
    result['type'] = 'rect'
    result['fps'] = round(seq.len / duration, 3)
    return result

class Sequence:
    def __init__(self,name):
        self.name = name

if __name__ == "__main__":
    dataset_folder = '/home/yiming/projects/mobiface_new/old/'
    with open(dataset_folder + 'SEQUENCES') as f:
        seqs = [Sequence(l.strip()) for l in f]
    for seq in seqs:
        seq.folder = os.path.join(dataset_folder, seq.name)
        seq.s_frames = sorted(glob.glob( seq.folder + '/img/*.png'))
        gt = np.loadtxt(seq.folder + '/groundtruth_rect.txt', delimiter=',')
        seq.len = len(gt)
        seq.init_rect = gt[0]
        results = run_ECO(seq, 0,0)
        savename = './results/' + seq.name + '_ECO.json'
        print('dumping results to ', savename)
        with open(savename, 'w') as f:
            json.dump(results, f, sort_keys=True, indent=2)

sequences.py

def get_sequence(seq, seq_home):
    img_dir = seq_home / seq / 'img'
    gt_path = seq_home / seq / 'groundtruth_rect.txt'
    img_list = list(img_dir.glob('*.jpg'))
    img_list.sort()
    with gt_path.open() as f:
        gt = np.loadtxt((x.replace(',',' ') for x in f))
    return img_list, gt[0], gt
  
  
  
# save to csv
import csv
with open('example.csv', 'w') as myFile:  
    myFields = ['rect', 'speed']
    writer = csv.DictWriter(myFile, fieldnames=myFields)    
    writer.writeheader()
    writer.writerow({'rect' : 'France', 'speed': 'Paris'})