2. Some context
• We build a platform allowing to
easily train and deploy custom
computer vision algorithms
• Our customers are mostly large
industrial groups
• Many different use-cases, one
methodology
4. My shopping list for deployment
Running locally
Reliability constraints
Bandwidth constraints
Privacy constraints
Various hardware requirements
High vs Low throughput
May need to be powered with 24V
May need to be as cheap as possible
State of the art
Various meta-architectures:
Caffe / TF / Darknet / ?Pytorch?
17. What’s next ? Workflows !
Image
Detector
Crop
Box 1 Label 1
Label 1 bisClassifier for « Label 1 »
Crop
Box N Label N
Label N bisClassifier for « Label 1 »
18. What’s next ? Workflows !
Image
Detector
Crop
Classifier for « Label 1 »
Box 1 Label 1
Label 1 bisClassifier for « Label 1 »
Classifier for « Label 1 »
Fuse
Crop
Classifier for « Label 1 »
Box N Label N
Label N bisClassifier for « Label 1 »
Classifier for « Label N »
Fuse
19. What’s next ? Workflows !
Image
Detector
Crop
Box K Label K
Label K bis
Classifier for « Label 1 »
Classifier for « Label 1 »
Classifier for « Label K »
Fuse
Jitter
Jitter
Jitter
20. What’s next ? Workflows !
Image
Detector
Crop
Box K Label K
Label K bis
Classifier for « Label 1 »
Classifier for « Label 1 »
Classifier for « Label K »
Fuse
Jitter
Jitter
Jitter
Tile
Box K Label K
Box K Label K
Box K Label K
Regroup