pil example detection PC (snippet)

Python pil example 'detection PC'

Functions in program:

• def detect_from_image():
• def detect_from_camera():

Modules used in program:

• import numpy as np
• import tensorflow as tf
• import cv2

python detection PC

Python pil example: detection PC

# -*- coding: utf-8 -*-
import cv2
import tensorflow as tf
import numpy as np

# https://www.tensorflow.org/lite/guide/hosted_models
# http://storage.googleapis.com/download.tensorflow.org/models/tflite/coco_ssd_mobilenet_v1_1.0_quant_2018_06_29.zip


def detect_from_camera():
    # load model
    interpreter = tf.lite.Interpreter(model_path="detect.tflite")
    interpreter.allocate_tensors()
    input_details = interpreter.get_input_details()
    output_details = interpreter.get_output_details()

    cap = cv2.VideoCapture(0) # 0はカメラのデバイス番号
    while True:
        # capture image
        ret, img_org = cap.read()
#        cv2.imshow('image', img_org)
        key = cv2.waitKey(1)
        if key == 27: # ESC
            break

        # prepara input image
        img = cv2.cvtColor(img_org, cv2.COLOR_BGR2RGB)
        img = cv2.resize(img, (300, 300))
        img = img.reshape(1, img.shape[0], img.shape[1], img.shape[2]) # (1, 300, 300, 3)
        img = img.astype(np.uint8)

        # set input tensor
        interpreter.set_tensor(input_details[0]['index'], img)

        # run
        interpreter.invoke()

        # get outpu tensor
        boxes = interpreter.get_tensor(output_details[0]['index'])
        labels = interpreter.get_tensor(output_details[1]['index'])
        scores = interpreter.get_tensor(output_details[2]['index'])
        num = interpreter.get_tensor(output_details[3]['index'])

        for i in range(boxes.shape[1]):
            if scores[0, i] > 0.5:
                box = boxes[0, i, :]
                x0 = int(box[1] * img_org.shape[1])
                y0 = int(box[0] * img_org.shape[0])
                x1 = int(box[3] * img_org.shape[1])
                y1 = int(box[2] * img_org.shape[0])
                box = box.astype(np.int)
                cv2.rectangle(img_org, (x0, y0), (x1, y1), (255, 0, 0), 2)
                cv2.rectangle(img_org, (x0, y0), (x0 + 100, y0 - 30), (255, 0, 0), -1)
                cv2.putText(img_org,
                       str(int(labels[0, i])),
                       (x0, y0),
                       cv2.FONT_HERSHEY_SIMPLEX,
                       1,
                       (255, 255, 255),
                       2)

    #    cv2.imwrite('output.jpg', img_org)
        cv2.imshow('image', img_org)

    cap.release()
    cv2.destroyAllWindows()


def detect_from_image():
    # prepara input image
    img_org = cv2.imread('input.jpg')
#    cv2.imshow('image', img)
    img = cv2.cvtColor(img_org, cv2.COLOR_BGR2RGB)
    img = cv2.resize(img, (300, 300))
    img = img.reshape(1, img.shape[0], img.shape[1], img.shape[2]) # (1, 300, 300, 3)
    img = img.astype(np.uint8)

    # load model
    interpreter = tf.lite.Interpreter(model_path="detect.tflite")
    interpreter.allocate_tensors()
    input_details = interpreter.get_input_details()
    output_details = interpreter.get_output_details()

    # set input tensor
    interpreter.set_tensor(input_details[0]['index'], img)

    # run
    interpreter.invoke()

    # get outpu tensor
    boxes = interpreter.get_tensor(output_details[0]['index'])
    labels = interpreter.get_tensor(output_details[1]['index'])
    scores = interpreter.get_tensor(output_details[2]['index'])
    num = interpreter.get_tensor(output_details[3]['index'])

    for i in range(boxes.shape[1]):
        if scores[0, i] > 0.5:
            box = boxes[0, i, :]
            x0 = int(box[1] * img_org.shape[1])
            y0 = int(box[0] * img_org.shape[0])
            x1 = int(box[3] * img_org.shape[1])
            y1 = int(box[2] * img_org.shape[0])
            box = box.astype(np.int)
            cv2.rectangle(img_org, (x0, y0), (x1, y1), (255, 0, 0), 2)
            cv2.rectangle(img_org, (x0, y0), (x0 + 100, y0 - 30), (255, 0, 0), -1)
            cv2.putText(img_org,
                   str(int(labels[0, i])),
                   (x0, y0),
                   cv2.FONT_HERSHEY_SIMPLEX,
                   1,
                   (255, 255, 255),
                   2)

#    cv2.imwrite('output.jpg', img_org)
    cv2.imshow('image', img_org)
    cv2.waitKey(0)
    cv2.destroyAllWindows()


if __name__ == '__main__':
    detect_from_camera()
    detect_from_image()

Python links

• Learn Python: https://pythonbasics.org/
• Python Tutorial: https://pythonprogramminglanguage.com