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import gradio as gr |
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import numpy as np |
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import cv2 |
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from ultralytics import YOLO |
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import base64 |
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class MeasureSize: |
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def __init__(self, img): |
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self.img = img |
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self.totalArea = 0 |
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self.totalObjects = 0 |
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def loadArucoSettings(self): |
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dictionary = cv2.aruco.getPredefinedDictionary(cv2.aruco.DICT_5X5_50) |
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parameters = cv2.aruco.DetectorParameters() |
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detector = cv2.aruco.ArucoDetector(dictionary, parameters) |
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corners, ids, rejected_img_points = detector.detectMarkers(self.img) |
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try: |
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aruco_perimeter = cv2.arcLength(corners[0], True) |
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except: |
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aruco_perimeter = 1 |
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return parameters, dictionary, corners, aruco_perimeter |
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def crop_square(img, size, interpolation=cv2.INTER_AREA): |
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h, w = img.shape[:2] |
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min_size = np.amin([h,w]) |
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crop_img = img[int(h/2-min_size/2):int(h/2+min_size/2), int(w/2-min_size/2):int(w/2+min_size/2)] |
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resized = cv2.resize(crop_img, (size, size), interpolation=interpolation) |
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return resized |
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def show_preds_image(pil_image): |
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img_original = np.array(pil_image) |
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img_original = img_original[:, :, ::-1].copy() |
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img = crop_square(img_original, 640) |
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ms = MeasureSize(img) |
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parameters, aruco_dict, corners, aruco_perimeter = ms.loadArucoSettings() |
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img = cv2.aruco.drawDetectedMarkers(img, corners) |
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return img, { |
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'aruco_perimeter': aruco_perimeter |
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} |
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if __name__ == '__main__': |
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outputs_image = [ |
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gr.components.Image(type="numpy", label="Output Image"), |
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gr.components.JSON() |
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] |
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interface_image = gr.Interface( |
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fn=show_preds_image, |
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inputs=gr.Image(type="pil"), |
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outputs=outputs_image, |
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title="ARUCO detector", |
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) |
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gr.TabbedInterface( |
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[interface_image], |
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tab_names=['Image inference'] |
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).queue().launch() |
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