# yolov3-ios

**Repository Path**: linkapp/yolov3-ios

## Basic Information

- **Project Name**: yolov3-ios
- **Description**: Using yolo v3 object detection on ios platform.
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2019-12-10
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# yolov3-ios
Using yolo v3 object detection on ios platform.

## Example applications:
![car](https://raw.githubusercontent.com/Mrlawrance/yolov3-ios/master/imgfolder/car.jpeg)

## QuickStart:
Run tiny_model.xcodeproj in ios.

## Training
The training process mainly consults [qqwweee/keras-yolo3](https://github.com/qqwweee/keras-yolo3). We add yolov3 with [Densnet](https://arxiv.org/pdf/1608.06993.pdf).

### 1.Requirement
* python 3.6.4
* keras 2.1.5
* tensorflow 1.6.0

### 2.Generate datasets
Generate datasets with VOC format. And try ```python voc_annotations```.

### 3.Start training
* ```cd yolov3_with_Densenet```

For yolo model with darknet:
* ```wget https://pjreddie.com/media/files/darknet53.conv.74```
* rename it as darknet53.weights
* ```python convert.py -w darknet53.cfg darknet53.weights model_data/darknet53_weights.h5```
* ```python yolov3_train.py```, with model_data/darknet53_weights.h5 as pre-trained model

For yolo model with densenet：
* ```python densenet_train.py```, with model_data/dense121_weights.h5 as pre-trained model


## Converting
### 1.Building environment
```
virtualenv -p /usr/bin/python2.7 keras_coreml_virt
source keras_coreml_virt/bin/activate
pip install protobuf
pip install tensorflow==1.6.0
pip install keras==2.1.5
pip install h5py
pip install coremltools==0.8.0
```

### 2.Convert .h5 model to .mlmodel
```python coreml.py```


## Building project in Xcode

* open tiny_model.xcodeproj with Xcode 9+
* change the .mlmodel file and Target Menmbership

For yolo model with darknet or densenet
* modify the code from line 43 to line 49 in YOLO.swift
* change the labels and the anchors in Helpers.swift
* run the project

For tiny model
* just change the labels and run the project