https://github.com/modelzoo/imageclassification
Image Classification Model implemented by ModelZoo
https://github.com/modelzoo/imageclassification
Last synced: about 1 month ago
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Image Classification Model implemented by ModelZoo
- Host: GitHub
- URL: https://github.com/modelzoo/imageclassification
- Owner: ModelZoo
- Created: 2018-10-05T17:48:01.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2019-11-16T19:04:31.000Z (over 5 years ago)
- Last Synced: 2025-03-28T01:48:53.186Z (about 2 months ago)
- Language: Python
- Homepage:
- Size: 13.7 KB
- Stars: 6
- Watchers: 0
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# ImageClassification
Image Classification Model implemented by [ModelZoo](https://github.com/ModelZoo/ModelZoo).
## Installation
Firstly you need to clone this repository and install dependencies with pip:
```
pip3 install -r requirements.txt
```
## Dataset
We use Fashion Mnist dataset for example.
## Usage
We can run this model like this:
```
python3 train.py
```
Outputs like this:
```
Epoch 1/20
1874/1875 [============================>.] - ETA: 0s - loss: 0.4318 - acc: 0.8427
1875/1875 [==============================] - 80s 43ms/step - loss: 0.4318 - acc: 0.8427 - val_loss: 0.3753 - val_acc: 0.8644
Epoch 2/20
1873/1875 [============================>.] - ETA: 0s - loss: 0.3295 - acc: 0.8777
Epoch 00002: saving model to checkpoints/model.ckpt
1875/1875 [==============================] - 82s 44ms/step - loss: 0.3295 - acc: 0.8777 - val_loss: 0.3684 - val_acc: 0.8716
Epoch 3/20
1872/1875 [============================>.] - ETA: 0s - loss: 0.2982 - acc: 0.8887
1875/1875 [==============================] - 70s 37ms/step - loss: 0.2984 - acc: 0.8887 - val_loss: 0.3563 - val_acc: 0.8726
Epoch 4/20
1873/1875 [============================>.] - ETA: 0s - loss: 0.2872 - acc: 0.8952
Epoch 00004: saving model to checkpoints/model.ckpt
1875/1875 [==============================] - 53s 28ms/step - loss: 0.2873 - acc: 0.8952 - val_loss: 0.3418 - val_acc: 0.8775
Epoch 5/20
1872/1875 [============================>.] - ETA: 0s - loss: 0.2679 - acc: 0.9000
1875/1875 [==============================] - 61s 33ms/step - loss: 0.2678 - acc: 0.9000 - val_loss: 0.3331 - val_acc: 0.8831
```
OK, we've finished training. Just so quickly.
## TensorBoard
Go to `events` folder, and run TensorBoard:
```
cd events
tensorboard --logdir=.
```
## Performance
Here is the benchmark of implemented models:
| Models | Eval Accuracy | Eval Loss |
| ------ | ------------- | --------- |
| FashionMnistModel | 0.8630 | 0.3945 |
## License
MIT