Image Classification model VGG16 from scratch | Computer Vision with Keras p.7

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Image Classification model VGG16 from scratch | Computer Vision with Keras p.7

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Күн бұрын

You can Build Computer Vision software to DETECT and TRACK any Object.
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We will see how to make the VGG16 model from scratch with Keras, I will enter all the steps until we arrive at the result with Keras.
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#keras #computervision #VGG16

Пікірлер: 56

@ghaithalmasri3039 Жыл бұрын

I can’t believe you’re doing this for free. You’re a legend

@bhushandeshpande7007 7 ай бұрын

I really love the playlist and I coded everything with you. I worked and tried to understand the VGG16 before, but no one explained this as easily and clearly as you. Thank you for your teaching. I am undergrad from Indian Institute of Science Education and Research (IISER) from India. I would like to communicate with you. Thank you once again.

@leo1722467 Жыл бұрын

The easiest way to understand for me so far, it's your vídeos. Ty for your effort.

@arduinouno1285 5 ай бұрын

Thanks a lot, this help me understand the concept without having to go too deep into the theory

@inhibited44 9 ай бұрын

Took coursera class in Machine Learning, but getting much more detail and more comfortable with this. Trying to model 200 pictures of 5 objects and not getting a match yet.

@cvicracer Жыл бұрын

Thanks for your videos,they really are well done. I always learn alot from them.

@pysource-com Жыл бұрын

glad to hear that ;)

@loganwoolfson5823 9 ай бұрын

Hi, I have tif images which are have 5 channels instead of the usual 3. How can I adapt the code to run these multispectral images? Any help would be greatly appreciated.@@pysource-com

@HariRavi Жыл бұрын

Great content. Keep publishing these contents. You explained everything clearly.

@Set1ish Жыл бұрын

Good job! My suggestion is to show how to train the model by using different picture cats, dogs, hedgehog to train the model and then test it on a new picture of dog and see the response of the model

@oliwiaroczniak4686 Жыл бұрын

Thank you very much please continue with this series

@ramikawamleh Жыл бұрын

many thanks for sharing, you have greate way for delivering the idea. hope to provide the training phase and focus on how to detect and avoid overfitting during training.

@pysource-com Жыл бұрын

slowly we will cover different aspects like training, image preprocessing, augmentation and so on.

@maheshikaharischandra490 8 ай бұрын

Excellent explanation, thank you.

@redabakkouch3764 Жыл бұрын

thanks man. love this playlist. hope to see more

@justinamichael316 Жыл бұрын

Extremely helpful...

@user-wm1ob3vs2t Жыл бұрын

Do you have a video(paid for or free) that shows how to train a model for specific categories and train it and then deploy it in python?

@nikostap 9 ай бұрын

Thanks for your video. Its soi interesting.

@VincentGonzales-zg6xg Жыл бұрын

Thank you this was very helpful!

@rezat3 4 ай бұрын

Very helpful. Thanks a lot.

@AxelWeber-gx2yt 3 ай бұрын

Thank you

@amrzakaria5290 Жыл бұрын

Good job , thank a lot.

@annyd3406 Жыл бұрын

that was very helpful thank u very much

@paul71249 10 ай бұрын

thank you bro

@ahmedhamdy-fz1lb Жыл бұрын

Thanks a lot, great video.

@shankar.parmargec5976 9 ай бұрын

very good video.. but I dont know hpw to use this model for classification.?

@leamon9024 Жыл бұрын

Thanks man! Love this series. Hope there's a video about how to tune a CNN model performance or tackle issue when data is imbalanced.

@goldiesmummy5008 Жыл бұрын

very nice work bro

@vvnchao Жыл бұрын

Thanks for the video 🎉

@eleojoadegbe Жыл бұрын

Thank you so much

@srijanairon4515 Жыл бұрын

when will the next video of th series be out it helped quite alot....

@marklawley3315 Жыл бұрын

Great video. How do you tell it that 1 is hedgehog, 2 is cat, and 3 is dog?

@ishaat_plays Жыл бұрын

Awesome Demonstration Sir. Could you make a video of Recurrent Neural Network for Computer vision in Real time Natural Language Processing ?

@pysource-com Жыл бұрын

I might do that in the future, but not soon as I'd like to show and explore more in depth Object Detection and Segmentation models

@daljeetsinghranawat6359 11 ай бұрын

i am working on mask rcnn in my post graduate degree.....i was wondering if i could impliment Faster RCNN from scratch....i know it uses RESNET which uses skip connection...........this video was very helpful in understanding out features are made...and one question that how output of last conv pooling layer...which has 7x7 images is mapped to first dense layer....i gues thats just (7x7x512)--->4096

@luukschalkwijk8043 7 ай бұрын

Can you also do identification with vgg16

@raj4624 Жыл бұрын

Brother your videos are so useful. Your instructions and teaching also top class . BTW your website not working while purchasing courses i tried multiple time but failed

@pysource-com Жыл бұрын

Hi Raj, thank you for your feedback. please contact me here sales1_academy@pysource.com and we'll assist you with that

@antonpivnenko6711 5 ай бұрын

good video

@mersibonmelese1262 9 ай бұрын

Great

@lioramar6420 Жыл бұрын

thanks for the video, can you teach us how to train a model that works fast on raspberry pi like the model.tflite?

@swatyk6881 Жыл бұрын

Thanks for this video…..

@cluelessarn Жыл бұрын

Thx

@neilyoung6671 Жыл бұрын

37:xx - I'm not getting the step from Dense(3) to hedgehog, cat, dog or Dense(2) to cat, dog. How is the number of units related to the category? Why is a Dense(3) not also car, trafficsign and people? Would you mind to explain?

@neilyoung6671 Жыл бұрын

Also: You get 0.39 for hedgehog, 0.18 for cat, 0.419 for dog, so basically the hedgehog was classified as dog?