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46 lines
1.9 KiB
46 lines
1.9 KiB
import cv2
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import numpy as np
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from Interfaces.RealSense import RealSenseController
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from Server.ServerProvider import RealSenseObjectDetectionServer
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def get_shot(controller):
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depth_matrix = controller.acquisition.get_depth_image()
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color_matrix = controller.acquisition.get_color_image()
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print(f"RS Data: {depth_matrix.shape}")
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return depth_matrix, color_matrix
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def draw_boxes_on_image(image, detections, target, follow_vector):
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for detection in detections:
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bbox = detection['bbox']
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class_name = detection['class_name']
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mean_depth = detection['mean_depth']
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x1, y1, x2, y2 = bbox
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color = (0, 0, 255) if detection == target else (0, 255, 0)
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cv2.rectangle(image, (x1, y1), (x2, y2), color, 2)
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label = f"{class_name}: {mean_depth:.2f} cm"
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cv2.putText(image, label, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)
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follow_text = f"Follow Vector: {follow_vector}"
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cv2.putText(image, follow_text, (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 255, 255), 2)
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return image
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def save_results(image, depth_matrix, filename="output_image.png", depth_filename="depth_matrix.npy"):
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cv2.imwrite(filename, image)
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print(f"Image saved as {filename}")
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np.save(depth_filename, depth_matrix)
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print(f"Depth matrix saved as {depth_filename}")
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if __name__ == "__main__":
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controller = RealSenseController()
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interface = RealSenseObjectDetectionServer()
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depth_matrix, color_matrix = get_shot(controller)
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response = interface.send_images(color_matrix, depth_matrix)
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if response:
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print("Ответ сервера:", response)
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detections_info = response.get("detections_info", [])
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target = response.get("target", {})
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follow_vector = response.get("follow_vector", [])
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color_matrix_with_boxes = draw_boxes_on_image(color_matrix.copy(), detections_info, target, follow_vector)
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save_results(color_matrix_with_boxes, depth_matrix) |