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https://github.com/prgrmcode/ai-image-classification-good-bad

This is a project to classify images from QA dataset from the AI4IM project.
https://github.com/prgrmcode/ai-image-classification-good-bad

cnn-classification deep-learning keras python3 tensorflow

Last synced: about 2 months ago
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This is a project to classify images from QA dataset from the AI4IM project.

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# AI-image-classification-Good-Bad

_This is a project to classify images from QA dataset from the AI4IM project._

Using QA camera images of injection moulded products.

The data set consists of QA images of (a part of the) products taken by 4 different cameras, from 4 different directions.

![classification](https://github.com/user-attachments/assets/318c66ff-73df-448a-a083-0036cd953fc6)

- The training images are labelled (grouped in different folders, by camera; good or bad).

---

![model accuracy](image.png)

![model loss](image-1.png)

---

![results](results.PNG)

---

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## to use locally; conda environment setup env_tf

### Tensorflow GPU on Windows Native

https://www.tensorflow.org/install/pip#windows-native:

```
conda create --name condaenv-tf python=3.9
conda activate condaenv-tf

conda install -c conda-forge cudatoolkit=11.2 cudnn=8.1.0
pip install --upgrade pip
```

### Anything above 2.10 is not supported on the GPU on Windows Native

```
pip install "tensorflow<2.11"
```

### Verify the GPU setup:

```
python -c "import tensorflow as tf; print(tf.config.list_physical_devices('GPU'))"
```

### Should return something like:

```
[PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')]
```