metadata
tags:
- image-classification
- pytorch
- computer-vision
- cup-detection
library_name: pytorch
Cup Detector - SmallCNN 2 Output
This model classifies a machine-specific ROI into:
- EMPTY
- CUP
- UNDEFINED
Model
- Architecture:
16 -> 32 -> 64 CNN - Input:
1 x 64 x 64 - Output layer:
2 - Loss:
BCEWithLogitsLoss
Output encoding
- EMPTY ->
[0, 0] - CUP ->
[1, 0] - UNDEFINED ->
[0, 1]
Output 0 represents CUP vs EMPTY.
Output 1 represents UNDEFINED.
Test Results
- Test Accuracy:
99.12% - Balanced Accuracy:
99.09% - CUP Precision:
98.73% - CUP Recall:
100.00% - EMPTY Specificity:
99.30% - CUP F1:
99.36%
Intended Pipeline
Camera / RTSP
↓
Machine-specific ROI
↓
Grayscale + Resize 64x64
↓
SmallCNN
↓
CUP / EMPTY / UNDEFINED
The ROI selection is handled outside the model. The model receives the cropped machine ROI.