python-kerasHow do I use Python and Keras to create an object detection system?

Object detection systems are used to detect objects in images or videos. Using Python and Keras, you can create an object detection system using a pre-trained model. Here is an example of using a pre-trained model to detect objects in an image:

# Import libraries
from keras.applications.mobilenet import MobileNet
from keras.preprocessing import image
from keras.applications.mobilenet import preprocess_input, decode_predictions
import numpy as np

# Load pre-trained model
model = MobileNet()

# Load an image
img_path = 'elephant.jpg'
img = image.load_img(img_path, target_size=(224, 224))

# Preprocess the image
x = image.img_to_array(img)
x = np.expand_dims(x, axis=0)
x = preprocess_input(x)

# Make a prediction
preds = model.predict(x)

# Decode the predictions
print('Predicted:', decode_predictions(preds, top=3)[0])

Output example

Predicted: [('n02504458', 'African_elephant', 0.85918015), ('n01871265', 'tusker', 0.0990826), ('n02504013', 'Indian_elephant', 0.039750935)]

The code above does the following:

1. Imports the necessary libraries (Keras, Numpy, etc.)
2. Loads a pre-trained model (in this case, MobileNet)
3. Loads an image
4. Preprocesses the image
5. Makes a prediction using the pre-trained model
6. Decodes the predictions

For more information on using Python and Keras for object detection, see the following links:

• Keras Object Detection
• Object Detection with Keras

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