The GUI is basically made to detect specific objects ie. Person, Cat, Dog, Chair, Bottle with a particular detection threshold.
The main backend used over here is the Tensorflow Object Detection API.
The TensorFlow Object Detection API is an open source framework built on top of TensorFlow that makes it easy to construct, train and deploy object detection models.
This GUI is made using PyQt5 and can work both in Ubuntu as well as in Windows.

Below are few Examples from the GUI

Tensorflow Object Detection API depends on the following libraries:

• Protobuf 3.0.0
• Python-tk
• Pillow 1.0
• lxml
• tf Slim (which is included in the "tensorflow/models/research/" checkout)
• Jupyter notebook
• Matplotlib
• Tensorflow (>=1.12.0)
• Cython
• contextlib2
• cocoapi

For detailed steps to install Tensorflow, follow the Tensorflow installation instructions. A typical user can install Tensorflow using one of the following commands:

# For CPU
pip install tensorflow
# For GPU
pip install tensorflow-gpu

The remaining libraries can be installed on Ubuntu using via apt-get:

sudo apt-get install protobuf-compiler python-pil python-lxml python-tk
pip install --user Cython
pip install --user contextlib2
pip install --user jupyter
pip install --user matplotlib

Alternatively, users can install dependencies using pip:

pip install --user Cython
pip install --user contextlib2
pip install --user pillow
pip install --user lxml
pip install --user jupyter
pip install --user matplotlib

3 different pre-trained object detection models of [COCO dataset] (http://mscoco.org) are being used in this Application.

1. ssd_mobilenet_v1_coco
2. ssd_mobilenet_v1_ppn_coco
3. faster_rcnn_inception_v2_coco

Note: If you download the tar.gz file of quantized models and un-tar, you will get different set of files - a checkpoint, a config file and tflite frozen graphs (txt/binary).

You can un-tar each tar.gz file via, e.g.,:

tar -xzvf ssd_mobilenet_v1_coco.tar.gz

Clone the complete repository and put the models downloaded in an new folder named Models inside the main folder.
And then run the following Command to use the application :

python main.py

Select the folder in which you have the images and use previous and next button to change the images
On the right hand side you have to select any model out of the 3 mentioned.
Set the detection threshold (0.6 suggested) and then select the objects u want to detect. Click on the Detect Button to see the output.

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to test the application properly first.