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# MobileNet v2 1.0 224 INT8
## Description
INT8 quantised version of MobileNet v2 model. Trained on ImageNet.
## License
[Apache-2.0](https://spdx.org/licenses/Apache-2.0.html)
## Related Materials
### Class Labels
The class labels associated with this model can be downloaded by running the script `get_class_labels.sh`.
### Model Recreation Code
Code to recreate this model can be found [here](recreate_model/).
## Network Information
| Network Information | Value |
|---------------------|----------------|
| Framework | TensorFlow Lite |
| SHA-1 Hash | 8de7996dfeadb5ab6f09e3114f3905fd03879eee |
| Size (Bytes) | 4020936 |
| Provenance | https://arxiv.org/pdf/1801.04381.pdf |
| Paper | https://arxiv.org/pdf/1801.04381.pdf |
## Performance
| Platform | Optimized |
|----------|:---------:|
| Cortex-A |:heavy_check_mark: |
| Cortex-M |:heavy_check_mark: |
| Mali GPU |:heavy_check_mark: |
| Ethos U |:heavy_check_mark: |
### Key
* :heavy_check_mark: - Will run on this platform.
* :heavy_multiplication_x: - Will not run on this platform.
## Accuracy
Dataset: ILSVRC 2012
| Metric | Value |
|--------|-------|
| Top 1 Accuracy | 0.697 |
## Optimizations
| Optimization | Value |
|--------------|---------|
| Quantization | INT8 |
## Network Inputs
<table>
<tr>
<th width="200">Input Node Name</th>
<th width="100">Shape</th>
<th width="300">Description</th>
</tr>
<tr>
<td>tfl.quantize</td>
<td>(1, 224, 224, 3)</td>
<td>Single 224x224 RGB image with INT8 values between -128 and 127</td>
</tr>
</table>
## Network Outputs
<table>
<tr>
<th width="200">Output Node Name</th>
<th width="100">Shape</th>
<th width="300">Description</th>
</tr>
<tr>
<td>MobilenetV2/Predictions/Reshape_11</td>
<td>(1, 1001)</td>
<td>Per-class confidence for 1001 ImageNet classes</td>
</tr>
</table>
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