| import cv2 |
| import base64 |
| import csv |
| import numpy as np |
| from pathlib import Path |
| from typing import List, Dict, Any |
|
|
| def draw_boxes(image: np.ndarray, detections: List[Dict[str, Any]]) -> np.ndarray: |
| """ |
| Draws bounding boxes and confidence labels on an image array based on detections. |
| |
| Inputs: |
| image: A numpy array representing the image (BGR format). |
| detections: A list of dictionaries, each containing 'xyxy' (list of [x1, y1, x2, y2]), |
| 'confidence' (float), and 'class_id' (int). |
| |
| Outputs: |
| A copy of the input numpy array with bounding boxes plotted. |
| |
| Side effects: |
| Does not mutate the original image array; returns a new annotated copy. |
| """ |
| img_copy = image.copy() |
| for det in detections: |
| |
| x1, y1, x2, y2 = map(int, det['xyxy']) |
| conf = det['confidence'] |
| |
| |
| label = f"Pothole: {conf:.2f}" |
| |
| |
| cv2.rectangle(img_copy, (x1, y1), (x2, y2), (0, 0, 255), 2) |
| |
| cv2.putText(img_copy, label, (x1, max(y1 - 10, 10)), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2) |
| |
| return img_copy |
|
|
| def image_to_base64(image: np.ndarray) -> str: |
| """ |
| Converts a numpy image array to a base64 encoded string. |
| |
| Inputs: |
| image: A numpy array representing the image. |
| |
| Outputs: |
| A base64 encoded string of the compressed PNG version of the image. |
| |
| Side effects: |
| None. |
| """ |
| success, buffer = cv2.imencode('.png', image) |
| if not success: |
| return "" |
| b64_str = base64.b64encode(buffer).decode('utf-8') |
| return b64_str |
|
|
| def export_csv(detections: List[Dict[str, Any]], export_path: str | Path) -> None: |
| """ |
| Writes a list of detection dictionaries to a CSV file. |
| |
| Inputs: |
| detections: A list of detection dictionaries containing flattened key-value pairs |
| (e.g., filename, confidence, latitude, etc.). |
| export_path: The file path (string or pathlib.Path) where the CSV will be saved. |
| |
| Outputs: |
| None. |
| |
| Side effects: |
| Creates or overwrites a file at the specified absolute export_path. |
| Creates parent directories iteratively if they do not exist. |
| """ |
| file_path = Path(export_path) |
| |
| file_path.parent.mkdir(parents=True, exist_ok=True) |
| |
| if not detections: |
| file_path.touch() |
| return |
|
|
| |
| keys = list(detections[0].keys()) |
| |
| with file_path.open('w', newline='', encoding='utf-8') as f: |
| dict_writer = csv.DictWriter(f, fieldnames=keys) |
| dict_writer.writeheader() |
| dict_writer.writerows(detections) |
|
|
