Initial Commit

Face Detection using YoloV3/ReadMe.txt

@@ -0,0 +1,62 @@
+# YOLOFace
+
+# Deep learning based Face detection using the YOLOv3 algorithm
+
+
+## Getting started
+
+The YOLOv3 (You Only Look Once) is a state-of-the-art, real-time object detection algorithm. The published model recognizes 80 different objects in images and videos. For more details, you can refer to this [paper](https://pjreddie.com/media/files/papers/YOLOv3.pdf).
+
+## YOLOv3's architecture
+
+![Imgur](assets/yolo-architecture.png)
+
+
+## OpenCV Deep Neural Networks (dnn module)
+
+OpenCV `dnn` module supports running inference on pre-trained deep learning models from popular frameworks such as TensorFlow, Torch, Darknet and Caffe.
+
+## Prerequisites
+
+* Tensorflow
+* opencv-python
+* opencv-contrib-python
+* Numpy
+* Keras
+* Matplotlib
+* Pillow
+
+Development for this project will be isolated in Python virtual environment. This allows us to experiment with different versions of dependencies.
+
+There are many ways to install `virtual environment (virtualenv)`, see the [Python Virtual Environments: A Primer](https://realpython.com/python-virtual-environments-a-primer/) guide for different platforms, but here are a couple:
+
+
+Create a Python 3.6 virtual environment for this project and activate the virtualenv:
+```bash
+$ virtualenv -p python3.6 yoloface
+$ source ./yoloface/bin/activate
+```
+
+Next, install the dependencies for the this project:
+```bash
+$ pip install -r requirements.txt
+```
+
+## Usage
+
+* Clone this repository
+
+* For face detection, you should download the pre-trained YOLOv3 weights file which trained on the [WIDER FACE: A Face Detection Benchmark](http://mmlab.ie.cuhk.edu.hk/projects/WIDERFace/index.html) dataset from this [link](https://drive.google.com/file/d/1xYasjU52whXMLT5MtF7RCPQkV66993oR/view?usp=sharing) and place it in the `model-weights/` directory.
+
+* Run the following command:
+
+>**image input**
+```bash
+$ python yoloface.py --image samples/outside_000001.jpg --output-dir outputs/
+```
+
+
+
+## Sample outputs
+
+![Imgur](assets/outside_000001_yoloface.jpg)

Face Detection using YoloV3/cfg/face.names

@@ -0,0 +1 @@
+face

Face Detection using YoloV3/cfg/face_classes.txt

@@ -0,0 +1 @@
+face

Face Detection using YoloV3/cfg/yolo_anchors.txt

@@ -0,0 +1 @@
+10,13,  16,30,  33,23,  30,61,  62,45,  59,119,  116,90,  156,198,  373,326