---
language: en
library_name: keras
tags:
- image-classification
- transfer-learning
- computer-vision
- keras
- tensorflow
- multiclass-classification
license: mit
datasets:
- custom
model-type: multi-model-repository
author: Thyagharajan K K
pipeline_tag: image-classification
inference: true
app_file: app.py
---

# 🧠 KKT-HF-TransferLearning-Models
  
## **Ready-to-Use Transfer Learning Models for Image Classification**

**Created by [Thyagharajan K K](https://huggingface.co/kkthyagharajan)**

[![Hugging Face Hub](https://img.shields.io/badge/HuggingFace-Repository-orange?logo=huggingface)](https://huggingface.co/kkthyagharajan/KKT-HF-TransferLearning-Models)
[![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](https://opensource.org/licenses/MIT)
[![Made with Keras](https://img.shields.io/badge/Made%20with-Keras-red?logo=keras)](https://keras.io/)
[![TensorFlow](https://img.shields.io/badge/Framework-TensorFlow-orange?logo=tensorflow)](https://www.tensorflow.org/)
[![KKT_DL_Package](https://img.shields.io/badge/Package-KKT__DL__Package-blue?logo=python)](https://github.com/kkthyagharajan/KKT_DL_Package)

---

## 📘 Overview  
This repository hosts a **collection of pretrained image-classification models** created using **Transfer Learning** in Keras/TensorFlow.  
Each subdirectory contains:  
- A trained `.keras` model file  
- A `class_names.txt` file  
- A `Test` folder with example test images  

You can use these models **programmatically** or through an **interactive demo app** powered by Gradio or Streamlit.

---

## 🧩 Programmatic Usage

```python
from KKT_DL_Package.utils.KKT_predictions import (
    multiclass_prediction_return,
    display_images_gui,
    get_hf_model_img_labels_local_path,
)

IMG_SIZE = (300, 300)

model_full_path, test_folder_path, class_names = (
    get_hf_model_img_labels_local_path(
    "kkthyagharajan/KKT-HF-TransferLearning-Models",
    IMG_SIZE,
    force_refresh=False,  # Won’t redownload if cached
    )
)

# Run predictions and display results
all_image_paths, all_predicted_labels, all_confidences = (
    multiclass_prediction_return(
        model_full_path,
        test_folder_path,
        class_names,
        IMG_SIZE,
    )
)

display_images_gui(
    all_image_paths,
    all_predicted_labels,
    IMG_SIZE,
)
```
---

## 🚀 Interactive Demo App  

### 🧩 Option 1: Run directly on Hugging Face  
This Space includes a web app defined by `app.py`.
### 💻 Option 2: Run locally using Gradio or Streamlit
  
```bash
pip install -r requirements.txt
python app.py   # or
streamlit run app.py
```

---

## 📁 Repository Structure

```

KKT-HF-TransferLearning-Models/          ← Root directory (your HF repo root)
│
├── Insect_Inception_V3/                 ← Model 1 directory
│   ├── insect_inception_v3_model.keras  ← Saved model file
│   ├── class_names.txt                  ← Corresponding class labels
│   └── InsectTest/                      ← Test image folder
│       ├── image_001.jpg
│       ├── image_002.jpg
│       └── ...
│
├── Insect_MobileNetV2/               ← Model 2 directory (example)
│   ├── insect_mobilenet_v2_model.keras
│   ├── class_names.txt
│   └── InsectTest/
│       ├── test1.jpg
│       ├── test2.jpg
│       └── ...
│
├── Insect_ResNet50/
│   ├── insect_resnet50_model.keras
│   ├── class_names.txt
│   └── InsectTest/
│       ├── imgA.jpg
│       ├── imgB.jpg
│       └── ...
│
└── README.md                            

```