Open-CV-Implementations

Author: altruistcoder

README.md

@@ -69,3 +69,7 @@ This is a repository of code files which can be used to perform some basic tasks
 * [Face and Eye Detection](https://github.com/altruistcoder/Open-CV-Implementations/blob/master/face_and_eye_detection.ipynb):
 
  Python Code to detect faces and eyes present in a video using OpenCV.
+
+* [Taking Timelapse](https://github.com/altruistcoder/Open-CV-Implementations/blob/master/timelapse.ipynb):
+
+ Python Code to take a Timelapse Video using OpenCV.

timelapse.ipynb

@@ -0,0 +1,186 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import os\n",
+ "import numpy as np\n",
+ "import cv2\n",
+ "import time\n",
+ "import datetime\n",
+ "import glob"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def image_resize(image, width = None, height = None, inter = cv2.INTER_AREA):\n",
+ " dim = None\n",
+ " (h, w) = image.shape[:2]\n",
+ " if width is None and height is None:\n",
+ " return image\n",
+ " if width is None:\n",
+ " r = height / float(h)\n",
+ " dim = (int(w * r), height)\n",
+ " else:\n",
+ " r = width / float(w)\n",
+ " dim = (width, int(h * r))\n",
+ "\n",
+ " resized_image = cv2.resize(image, dim, interpolation = inter)\n",
+ " return resized_image\n",
+ "\n",
+ "\n",
+ "class MyVideoConf(object):\n",
+ " STD_DIMENSIONS = {\n",
+ " \"360p\": (480, 360),\n",
+ " \"480p\": (640, 480),\n",
+ " \"720p\": (1280, 720),\n",
+ " \"1080p\": (1920, 1080),\n",
+ " \"4k\": (3840, 2160),\n",
+ " }\n",
+ " # Types of Codes: http://www.fourcc.org/codecs.php\n",
+ " VIDEO_TYPE = {\n",
+ " 'avi': cv2.VideoWriter_fourcc(*'XVID'),\n",
+ " 'mp4': cv2.VideoWriter_fourcc(*'XVID'),\n",
+ " }\n",
+ " width = 640\n",
+ " height = 480\n",
+ " dims = (640, 480)\n",
+ " capture = None\n",
+ " video_type = None\n",
+ " def __init__(self, capture, filepath, res=\"480p\", *args, **kwargs):\n",
+ " self.capture = capture\n",
+ " self.filepath = filepath\n",
+ " self.width, self.height = self.get_dims(res=res)\n",
+ " self.video_type = self.get_video_type()\n",
+ " \n",
+ " def change_res(self, width, height):\n",
+ " self.capture.set(3, width)\n",
+ " self.capture.set(4, height)\n",
+ "\n",
+ " def get_dims(self, res='480p'):\n",
+ " width, height = self.STD_DIMENSIONS['480p']\n",
+ " if res in self.STD_DIMENSIONS:\n",
+ " width, height = self.STD_DIMENSIONS[res]\n",
+ " self.change_res(width, height)\n",
+ " self.dims = (width, height)\n",
+ " return width, height\n",
+ "\n",
+ " def get_video_type(self):\n",
+ " filename, ext = os.path.splitext(self.filepath)\n",
+ " if ext in self.VIDEO_TYPE:\n",
+ " return self.VIDEO_TYPE[ext]\n",
+ " return self.VIDEO_TYPE['avi']"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "cap = cv2.VideoCapture(0)\n",
+ "\n",
+ "frames_per_seconds = 20\n",
+ "save_path = 'timelapse.avi'\n",
+ "config = MyVideoConf(cap, filepath=save_path, res='720p')\n",
+ "out = cv2.VideoWriter(save_path, config.video_type, frames_per_seconds, config.dims)\n",
+ "\n",
+ "seconds_duration = 50\n",
+ "seconds_between_shots = 5\n",
+ "timelapse_img_dir = \"images_timelapse/\"\n",
+ "\n",
+ "if not os.path.exists(timelapse_img_dir):\n",
+ " os.mkdir(timelapse_img_dir)\n",
+ "\n",
+ "now = datetime.datetime.now()\n",
+ "finish_time = now + datetime.timedelta(seconds=seconds_duration)\n",
+ "\n",
+ "i = 0\n",
+ "\n",
+ "while datetime.datetime.now() < finish_time:\n",
+ " ret, frame = cap.read()\n",
+ " filename = \"{0}/{1}.jpg\".format(timelapse_img_dir, i)\n",
+ " i += 1\n",
+ " cv2.imwrite(filename, frame)\n",
+ " cv2.imshow('frame', frame)\n",
+ " time.sleep(seconds_between_shots)\n",
+ " if cv2.waitKey(20) & 0xFF == ord('q'):\n",
+ " break\n",
+ "\n",
+ "clear_images = True\n",
+ "\n",
+ "def images_to_video(out, image_dir, clear_images=True):\n",
+ " image_list = glob.glob(\"{0}/*.jpg\".format(image_dir))\n",
+ " sorted_images = sorted(image_list, key=os.path.getmtime)\n",
+ " for file in sorted_images:\n",
+ " image_frame = cv2.imread(file)\n",
+ " out.write(image_frame)\n",
+ " if clear_images:\n",
+ " # Remove stored timelapse images\n",
+ " for file in image_list:\n",
+ " os.remove(file)\n",
+ "\n",
+ "images_to_video(out, timelapse_img_dir, clear_images=True)\n",
+ "\n",
+ "cap.release()\n",
+ "cv2.destroyAllWindows()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.5.2"
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+ "nbformat_minor": 2
+}