yinguobing

n=0
for i in *
do
  if [ $((n+=1)) -gt 50 ]; then
    n=1
  fi
  todir=../my_file$n
  [ -d "$todir" ] || mkdir "$todir" 
  mv "$i" "$todir" 
done

yinguobing

"""Template code for video frame processing.

Features:
    - video source from files or webcams.
    - automatically flip the frame if reading from webcam.
    - built in video writer to output the processed result.
    - built in FPS metter.

For more: https://github.com/yinguobing
"""

yinguobing

import tkinter

import cv2
import matplotlib
from matplotlib import animation, pyplot
from mpl_toolkits.mplot3d import Axes3D

# The module mesh_detector could be found here:
# https://github.com/yinguobing/head-pose-estimation/tree/google-face-mesh
from mesh_detector import MeshDetector

yinguobing

"""Imports a SavedModel as a graph in Tensorboard."""

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import argparse
import sys

from tensorflow.core.framework import graph_pb2

yinguobing

import tensorflow as tf

MODEL_PATH = '/home/robin/Desktop/arc_inf/1554262166'
IMAGE_PATH = '/data/dataset/public/ms_celeb_1m/arc_face_data/img/0/0.jpg'

with tf.Session(graph=tf.Graph()) as sess:
    # Restore model from the saved_modle file, that is exported by TensorFlow estimator.
    tf.saved_model.loader.load(sess, ["serve"], MODEL_PATH)

    # Get the output node from the graph.

yinguobing

"""Minimal example showing how to generate TensorFlow TFRecord file."""

import tensorflow as tf
tf.enable_eager_execution()


# All raw values should be converted to a type compatible with tf.Example. Use
# the following functions to do these convertions.
def _bytes_feature(value):
    """Returns a bytes_list from a string / byte."""

yinguobing

import matplotlib.pyplot as plt
import numpy as np

DURATION = 12
FPS = 25
START = 0
STEPS = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]


if __name__ == "__main__":

yinguobing

"""
read() and grab() in OpenCV VideoCapture takes different time as there is no
decoding for grab() operation. Let's try to find out how much these two methods
differs.
"""
import cv2


def main():
    tm = cv2.TickMeter()

yinguobing

# Original code here:
# https://github.com/opencv/opencv/blob/master/samples/python/video_threaded.py

#!/usr/bin/env python3

'''
Multithreaded video processing minimal sample.
Usage:
   python3 video_threaded.py
   Shows how python threading capabilities can be used

yinguobing

import os
import numpy
from random import randint
from PIL import Image

# Get all the image files' path.
homePath = "./images"

# Define locations for different type of data.
for dir_parent in ["train", "test"]: