See full course on Object Detection: ua-cam.com/play/PL1GQaVhO4f_jLxOokW7CS5kY_J1t1T17S.html and Subscribe to my channel If you found this tutorial useful, please share with your friends(WhatsApp/iMessage/Messenger/WeChat/Line/KaTalk/Telegram) and on Social(LinkedIn/Quora/Reddit), Tag @cogneethi on twitter.com Let me know your feedback @ cogneethi.com/contact
It is just your network design. If you use different input dimension, you will have to adjust the Fully Connected layers accordingly. This will get clearer as you progress through the course, esp the OverFeat chapter.
See full course on Object Detection: ua-cam.com/play/PL1GQaVhO4f_jLxOokW7CS5kY_J1t1T17S.html and Subscribe to my channel
If you found this tutorial useful, please share with your friends(WhatsApp/iMessage/Messenger/WeChat/Line/KaTalk/Telegram) and on Social(LinkedIn/Quora/Reddit),
Tag @cogneethi on twitter.com
Let me know your feedback @ cogneethi.com/contact
Very informative 👍 Thank you for clarifying doubts 🙏 Keep it up
Excellent 👌!
Thanks ✌️
Hello sir,
Can you please tell me some algorithms for detecting multiple faces/objects in an image???
And how to extract them (faces).
Depending on the use case, you can try any of Viola Jones, DLib, OpenCV, MTCNN, FaceNet or InsightFace.
Why we take input image size 224x224 ? why not 225x225
It is just your network design. If you use different input dimension, you will have to adjust the Fully Connected layers accordingly.
This will get clearer as you progress through the course, esp the OverFeat chapter.
Brilliant video !
Thank you!
can you also share notebooks/code for these
Great video 👍🏻
drive.google.com/drive/folders/120KC9i3F0WMhqksngS-dWS1iJNP-mXAv?usp=sharing
Could you please share the code related to the whole series.
drive.google.com/drive/folders/120KC9i3F0WMhqksngS-dWS1iJNP-mXAv?usp=sharing
github.com/endernewton/tf-faster-rcnn