Firebase ML Kit: Pre-Trained Models
I can see there are 3 pre-trained models included in the assets folder of the ML-Kit sample app.
Please help me understand
- Which of these models correspond to face detection?
- What is the data set used to train these models?
android tensorflow face-detection tensorflow-lite firebase-mlkit edited Nov 16 at 12:27
Fantômas
32.3k156288
asked Nov 16 at 9:36
Subhash_Reddy
90113
add a comment |
I can see there are 3 pre-trained models included in the assets folder of the ML-Kit sample app.
Please help me understand
- Which of these models correspond to face detection?
- What is the data set used to train these models?
android tensorflow face-detection tensorflow-lite firebase-mlkit edited Nov 16 at 12:27
Fantômas
32.3k156288
asked Nov 16 at 9:36
Subhash_Reddy
90113
add a comment |
I can see there are 3 pre-trained models included in the assets folder of the ML-Kit sample app.
Please help me understand
- Which of these models correspond to face detection?
- What is the data set used to train these models?
android tensorflow face-detection tensorflow-lite firebase-mlkit edited Nov 16 at 12:27
Fantômas
32.3k156288
asked Nov 16 at 9:36
Subhash_Reddy
90113
I can see there are 3 pre-trained models included in the assets folder of the ML-Kit sample app.
Please help me understand
- Which of these models correspond to face detection?
- What is the data set used to train these models?
android tensorflow face-detection tensorflow-lite firebase-mlkit android tensorflow face-detection tensorflow-lite firebase-mlkit edited Nov 16 at 12:27
Fantômas
32.3k156288
asked Nov 16 at 9:36
Subhash_Reddy
90113
edited Nov 16 at 12:27
Fantômas
32.3k156288
asked Nov 16 at 9:36
Subhash_Reddy
90113
edited Nov 16 at 12:27
Fantômas
32.3k156288
edited Nov 16 at 12:27
Fantômas
32.3k156288
edited Nov 16 at 12:27
Fantômas
32.3k156288
32.3k156288
asked Nov 16 at 9:36
Subhash_Reddy
90113
asked Nov 16 at 9:36
Subhash_Reddy
90113
asked Nov 16 at 9:36
Subhash_Reddy
90113
90113
add a comment |
add a comment |
1 Answer
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Those are custom models provided to highlight the ML Kit functionality that allows you to bring your own TFLite models.
The pre-trained APIs, also known as Base APIs (text recognition, image labeling, etc) get added by including the appropriate libraries in your app's gradle file. No need to include anything in your assets folder. See an example here:
https://firebase.google.com/docs/ml-kit/android/recognize-text
answered Dec 4 at 13:54
Sachin K
197212
add a comment |
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1 Answer
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1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
Those are custom models provided to highlight the ML Kit functionality that allows you to bring your own TFLite models.
The pre-trained APIs, also known as Base APIs (text recognition, image labeling, etc) get added by including the appropriate libraries in your app's gradle file. No need to include anything in your assets folder. See an example here:
https://firebase.google.com/docs/ml-kit/android/recognize-text
answered Dec 4 at 13:54
Sachin K
197212
add a comment |
Those are custom models provided to highlight the ML Kit functionality that allows you to bring your own TFLite models.
The pre-trained APIs, also known as Base APIs (text recognition, image labeling, etc) get added by including the appropriate libraries in your app's gradle file. No need to include anything in your assets folder. See an example here:
https://firebase.google.com/docs/ml-kit/android/recognize-text
answered Dec 4 at 13:54
Sachin K
197212
add a comment |
Those are custom models provided to highlight the ML Kit functionality that allows you to bring your own TFLite models.
The pre-trained APIs, also known as Base APIs (text recognition, image labeling, etc) get added by including the appropriate libraries in your app's gradle file. No need to include anything in your assets folder. See an example here:
https://firebase.google.com/docs/ml-kit/android/recognize-text
answered Dec 4 at 13:54
Sachin K
197212
Those are custom models provided to highlight the ML Kit functionality that allows you to bring your own TFLite models.
The pre-trained APIs, also known as Base APIs (text recognition, image labeling, etc) get added by including the appropriate libraries in your app's gradle file. No need to include anything in your assets folder. See an example here:
https://firebase.google.com/docs/ml-kit/android/recognize-text
answered Dec 4 at 13:54
Sachin K
197212
answered Dec 4 at 13:54
Sachin K
197212
answered Dec 4 at 13:54
Sachin K
197212
answered Dec 4 at 13:54
Sachin K
197212
197212
add a comment |
add a comment |
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