---
language:
- en
pipeline_tag: image-classification
---
# Simple Object Detection App

Convolution Network trained with CIFER-10 data set.  
- Accuracy: 0.7875  
- Loss: 0.6094

Model: "sequential"
| Layer (type)                | Output Shape       | Param #   |
|-----------------------------|--------------------|-----------|
| conv2d (Conv2D)             | (None, 30, 30, 32) | 896       |
| max_pooling2d (MaxPooling2D) | (None, 15, 15, 32) | 0         |
| conv2d_1 (Conv2D)           | (None, 13, 13, 64) | 18,496    |
| max_pooling2d_1 (MaxPooling2D) | (None, 6, 6, 64)   | 0         |
| flatten (Flatten)           | (None, 2304)       | 0         |
| dense (Dense)               | (None, 64)         | 147,520   |
| dense_1 (Dense)             | (None, 10)         | 650       |

 Total params: 502,688 (1.92 MB)  
 Trainable params: 167,562 (654.54 KB)  
 Non-trainable params: 0 (0.00 B)  
 Optimizer params: 335,126 (1.28 MB)