keras-object-detection-web-api

A simple wrapper over keras object detection libraries and provide web api using flask

Usage

Detect objects in an image using YOLO algorithm

The demo code below can be found in keras_object_detection/demo/yolo_predict.py

The demo codes takes in the image keras_object_detection/demo/images/test.jpg and output the detected boxes with class labels

import os

import scipy
from matplotlib.pyplot import imshow

from keras_object_detection.library.yolo import YoloObjectDetector
from keras_object_detection.library.yolo_utils import generate_colors, draw_boxes

model_dir_path = 'keras_object_detection/models'

image_file = 'keras_object_detection/demo/images/test.jpg'

detector = YoloObjectDetector()
detector.load_model(model_dir_path)

image, out_scores, out_boxes, out_classes = detector.predict(image_file)

# Print predictions info
print('Found {} boxes for {}'.format(len(out_boxes), image_file))
# Generate colors for drawing bounding boxes.
colors = generate_colors(detector.class_names)
# Draw bounding boxes on the image file
draw_boxes(image, out_scores, out_boxes, out_classes, detector.class_names, colors)
# Save the predicted bounding box on the image
image.save("keras_object_detection/demo/out/images/test.jpg", quality=90)
output_image = scipy.misc.imread("keras_object_detection/demo/out/images/test.jpg")
imshow(output_image)

Below is the image before detection:

Here is the image after detection: