Hello, thank you so much for the video can i apply RSNET-50 network instead of your model? i am newbie to deep lerning topic and i need to do something different for my project. thanks in advance
man..can u share...th model that u built using ur own dataset and replacing in last five minutes?? the antispoofing model that u uploaded isnt accurate...i need th one that u build hede with lots of function...
please prepare the dataset for your own and do the training as the training is done in the video... for improvement results... This is not the state of the art solution... It works for webcam and for mobile phone attack... not tested on tablet... and other use cases...
hello brother , it is also displaying as real for photos, and in toggling between real and spoof for mobile photos. I think the model is trained such that it detects spoof only if photos are too bright or blurry. brother pls help me with a solution
hey. wat was the solution for this .m facing same issue that u face....even m not able to get the th model he is building in this video...i think..th model he is buildng seems more accurate...
For live image : Use webcam to capture continuous 50 frames For spoof image : For photo attack: Use webcam to capture continuous 50 frames from mobile photos For replay attack: Use a short video from mobile and start a webcam to capture these moments
Thank you for posting very nice content. All the best for future projects and innovations. Keep learning keep contributing for IT society🇳🇵
Thank you.... You are doing great as well....
@@prabhatale1135Brother please help me mei learning Exam de rha hu tb face spoof detection aa rha h plz help me mera no dp pr diya h 😢😢🙏🙏🙏
Are there any other datasets available like this. Could someone share the dataset reference if you have 😢
wow, great dai
Last five minutes you changed,that file needed...?
the file named original vs new_dataset.png is not in dataset from where you picked this file
Training accuracy is lesser than the validation accuracy, is this fine ? I'm a newbie.
Hello, thank you so much for the video
can i apply RSNET-50 network instead of your model? i am newbie to deep lerning topic and i need to do something different for my project. thanks in advance
Hello, what algorithm did you use?
Great job. but how you collected real and fake images in the given directories.
is this anti-spoofing system compatible with flask
hello... What algorithm does this work? and Article link ?
if we show video from mobile its detecting as real , how to fix that ?
why change the hexadecimal image size to 160x160
the liveliness code does not work on mac book
man..can u share...th model that u built using ur own dataset and replacing in last five minutes?? the antispoofing model that u uploaded isnt accurate...i need th one that u build hede with lots of function...
Yes,I need also
I run the code. It detected my faces but it didnt work. All fake faces in photos on my tablet screen are detected as a real face!
please prepare the dataset for your own and do the training as the training is done in the video... for improvement results... This is not the state of the art solution... It works for webcam and for mobile phone attack... not tested on tablet... and other use cases...
Cool 👍
hello brother , it is also displaying as real for photos, and in toggling between real and spoof for mobile photos.
I think the model is trained such that it detects spoof only if photos are too bright or blurry.
brother pls help me with a solution
hey. wat was the solution for this .m facing same issue that u face....even m not able to get the th model he is building in this video...i think..th model he is buildng seems more accurate...
how did you collected the spoof dataset?
For live image : Use webcam to capture continuous 50 frames
For spoof image :
For photo attack: Use webcam to capture continuous 50 frames from mobile photos
For replay attack: Use a short video from mobile and start a webcam to capture these moments
@@prabhatale1135is there anything we can do to automate the process of collecting data for spoof images ?
feasible to know, but not practical in reality. In truly face recoginition system, it's seem possible for engineer to collecting all fake images.
waht have me original vs new_dataset.png
I didnot understand what you are trying to say?
Hello, what algorithm did you use?