https://github.com/billy-enrizky/gr-cls-multitask-v2
Multi Task Neural Network for Grasping and Classification
https://github.com/billy-enrizky/gr-cls-multitask-v2
deep-learning deep-neural-networks neuroscience-inspired-ai
Last synced: 8 months ago
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Multi Task Neural Network for Grasping and Classification
- Host: GitHub
- URL: https://github.com/billy-enrizky/gr-cls-multitask-v2
- Owner: billy-enrizky
- Created: 2025-01-07T16:06:15.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2025-02-02T20:23:38.000Z (9 months ago)
- Last Synced: 2025-02-02T21:23:58.279Z (9 months ago)
- Topics: deep-learning, deep-neural-networks, neuroscience-inspired-ai
- Language: Python
- Homepage: https://billy-enrizky.github.io/gr-cls-multitask-v2/
- Size: 102 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# gr-cls-multitask
Multi-tasking model for grasping and classification (in progress)
you can see the model architecture in [multi_task_models/grcn_multi_alex.py](multi_task_models/grcn_multi_alex.py)
# RSA instructions
## First step is to download the matlab data!
Run this from inside the `matlab_files` directory
```
gdown --folder https://drive.google.com/drive/folders/1FBsL4MVpCpqCuobVhH1_23RLRHDfx0Y7?ths=true
```
## Running the RSA
```
python3 rsa.py [suffix of output file]
```
## multiAlexMap_top5_v1.5
Task| Recogniton | Grasping
--- | --- | ---
Train Accuracy (%) | 99.02 | 83.65
Test Accuracy (%) | 85.0| 81.5
Learning Rate | 301 | 283
Epoch | 150 | 150
Size of divergent heads: 4 layers
Weighted Loss Ratio (Grasp : Classification): 1.5 : 0.5
Epochs: 150
Batch Size: 5
Grasp Accuracies - Training: 83.65 - Test: 81.5
Classification Accuracies - Training: 99.02 - Test: 85.0
## multiAlexMap_top5_v1.4
Size of divergent heads: 4 layers
Weighted Loss Ratio (Grasp : Classification): 0.5 : 1.5
Epochs: 150
Batch Size: 5
Grasp Accuracies - Training: 77.9 - Test: 75.5
Classification Accuracies - Training: 97.98 - Test: 84.5
## multiAlexMap_top5_v1.3
Size of divergent heads: 4 layers
Epochs: 130
Batch Size: 5
Grasp Accuracies - Training: 79.95 - Test: 79.5
Classification Accuracies - Training: 98.17 - Test: 82.75
## multiAlexMap_top5_v1.2
Size of divergent heads: 1 layer
Epochs: 150
Batch Size: 2
Grasp Accuracies - Training: 72.4 - Test: 67.0
Classification Accuracies - Training: 98.53 - Test: 89.25
## multiAlexMap_top5_v1.1
Size of divergent heads: 1 layer
Epochs: 150
Batch Size: 5
Grasp Accuracies - Training: 72.22 - Test: 75.75
Classification Accuracies - Training: 98.5 - Test: 82.75