asrani1 / live-cctv Goto Github PK

WEEK 6 (ARNAV)

DAY 1: Implemented the cosine difference algorithm in video to calculate similarity between 2 consecutive frames of a video

DAY 2: Implemented euclidean distance and manhattan diatance to realtime video. The program was also set to record the video
if significant changes were detected in any frame

DAY 3: Tried to implement the YOLO algorithm with pretrained models for object detection

DAY 4: Implemented cv2 functions to detect object in an image and make a bounding box around it.

DAY 5: The code now detectes moving object in a realtime and also records if significant changes are detected in the frames of
the video

WEEK 2

DAY 1(13/09/21): Finished Linear algebra(16/16) and neural network(3/3) playlist (3B1B)
Held a meet with seniors regarding the project, ideas and the way to
move forward.

DAY 2(14/09/21): Saw some research papers on scene change detection. Will look for more
and finalize some to read.

DAY 3(15/09/21): Started with the Coursera course on Deep learning (first week).

DAY 4(16/09/21): Completed first week of the 1st course, started with the second week.

DAY 5(17/09/21): Completed the second week of the course and also downloaded VM ware and ubuntu
20.04 LTS and set it up. Had a meet with the mentor regarding the way
ahead with the project.

WEEK 1 (ARNAV)

Day 1: Applied for a financial aid in Deep learning course in Coursera.

Day 2: Started with Linear algebra playlist (https://www.youtube.com/watch?v=kYB8IZa5AuE)

Day 3: Linear algebra playlist continued

Day 4: Started with neural networks playlist(2/4)
(https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi
Continuation of linear algebra

Day 5: Made a git repository for "live-cctv".
Continued with linear algebra playlist (7/15)

WEEK 4 (ARNAV)

DAY 1: -

DAY 2: continued with coursera course on deep learning (completed week 2 and assignement).

DAY 3: Continued with coursera course on deep learining, put darknet in ubuntu.

DAY 4: Continued with coursera course (completed week 3 and assignment)

DAY 5: Continued with coursera course (week 4)

WEEK 5 (ARNAV)

DAY 1: Coursera course 4 started, also reading reasearch paper regarding the project.

DAY 2: Looked about YOLO and many more algorithms for object detection. Continued with the coursera course.
Learned more about openCV from various sources

DAY 3: Coursera course 4 week 1 completed with ideas of basic CNN.

DAY 4: Learned about Cosine similarity and implemented it to calculate similarity between 2 images. Started to study the YOLO
algorithm.

DAY 5: Studied YOLO algorithm and also read and implemented euclidean and manhattam distance for image similarity.