Object Detection

Object detection using ImageAI, all you need to do is

Install Python on your computer system
Install ImageAI and its dependencies
Download the Object Detection model file
Run the sample codes (which is as few as 10 lines)

Now let’s get started.

1. download and install python on your pc.

2. Install ImageAI and dependencies

- Tensorflow

pip install tensorflow==2.4.0

- Others

pip install keras==2.4.3 numpy==1.19.3 pillow==7.0.0 scipy==1.4.1 h5py==2.10.0 matplotlib==3.3.2 opencv-python keras-resnet==0.2.0

Install the ImageAI library

pip install imageai --upgrade

3. Download the RetinaNet model file that will be used for object detection via this link.

Great. Now that you have installed the dependencies, you are ready to write your first object detection code. Create a Python file and give it a name (For example, FirstDetection.py), and then write the code below into it. Copy the RetinaNet model file and the image you want to detect to the folder that contains the python file.

FirstDetection.py

	from imageai.Detection import ObjectDetection
	import os

	execution_path = os.getcwd()

	detector = ObjectDetection()
	detector.setModelTypeAsRetinaNet()
	detector.setModelPath( os.path.join(execution_path , "resnet50_coco_best_v2.1.0.h5"))
	detector.loadModel()
	detections = detector.detectObjectsFromImage(input_image=os.path.join(execution_path,"image.jpg"), output_image_path=os.path.join(execution_path , "imagenew.jpg"))

	for eachObject in detections:
	print(eachObject["name"] , " : " , eachObject["percentage_probability"] )

Then run the code and wait while the results prints in the console. Once the result is printed to the console, go to the folder in which your FirstDetection.py is and you will find a new image saved. Take a look at a 2 image samples below and the new images saved after detection.

Before Detection: