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@ -10,10 +10,44 @@ from ultralytics.utils.plotting import Annotator |
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class ParkingPtsSelection: |
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"""Class for selecting and managing parking zone points on images using a Tkinter-based UI.""" |
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""" |
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A class for selecting and managing parking zone points on images using a Tkinter-based UI. |
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This class provides functionality to upload an image, select points to define parking zones, and save the |
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selected points to a JSON file. It uses Tkinter for the graphical user interface. |
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Attributes: |
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tk (module): The Tkinter module for GUI operations. |
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filedialog (module): Tkinter's filedialog module for file selection operations. |
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messagebox (module): Tkinter's messagebox module for displaying message boxes. |
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master (tk.Tk): The main Tkinter window. |
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canvas (tk.Canvas): The canvas widget for displaying the image and drawing bounding boxes. |
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image (PIL.Image.Image): The uploaded image. |
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canvas_image (ImageTk.PhotoImage): The image displayed on the canvas. |
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rg_data (List[List[Tuple[int, int]]]): List of bounding boxes, each defined by 4 points. |
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current_box (List[Tuple[int, int]]): Temporary storage for the points of the current bounding box. |
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imgw (int): Original width of the uploaded image. |
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imgh (int): Original height of the uploaded image. |
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canvas_max_width (int): Maximum width of the canvas. |
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canvas_max_height (int): Maximum height of the canvas. |
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Methods: |
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setup_ui: Sets up the Tkinter UI components. |
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initialize_properties: Initializes the necessary properties. |
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upload_image: Uploads an image, resizes it to fit the canvas, and displays it. |
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on_canvas_click: Handles mouse clicks to add points for bounding boxes. |
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draw_box: Draws a bounding box on the canvas. |
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remove_last_bounding_box: Removes the last bounding box and redraws the canvas. |
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redraw_canvas: Redraws the canvas with the image and all bounding boxes. |
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save_to_json: Saves the bounding boxes to a JSON file. |
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Examples: |
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>>> parking_selector = ParkingPtsSelection() |
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>>> # Use the GUI to upload an image, select parking zones, and save the data |
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""" |
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def __init__(self): |
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"""Class initialization method.""" |
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"""Initializes the ParkingPtsSelection class, setting up UI and properties for parking zone point selection.""" |
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check_requirements("tkinter") |
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import tkinter as tk |
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from tkinter import filedialog, messagebox |
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@ -24,7 +58,7 @@ class ParkingPtsSelection: |
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self.master.mainloop() |
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def setup_ui(self): |
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"""Sets up the Tkinter UI components.""" |
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"""Sets up the Tkinter UI components for the parking zone points selection interface.""" |
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self.master = self.tk.Tk() |
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self.master.title("Ultralytics Parking Zones Points Selector") |
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self.master.resizable(False, False) |
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@ -45,14 +79,14 @@ class ParkingPtsSelection: |
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self.tk.Button(button_frame, text=text, command=cmd).pack(side=self.tk.LEFT) |
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def initialize_properties(self): |
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"""Initialize the necessary properties.""" |
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"""Initialize properties for image, canvas, bounding boxes, and dimensions.""" |
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self.image = self.canvas_image = None |
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self.rg_data, self.current_box = [], [] |
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self.imgw = self.imgh = 0 |
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self.canvas_max_width, self.canvas_max_height = 1280, 720 |
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def upload_image(self): |
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"""Uploads an image, resizes it to fit the canvas, and displays it.""" |
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"""Uploads and displays an image on the canvas, resizing it to fit within specified dimensions.""" |
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from PIL import Image, ImageTk # scope because ImageTk requires tkinter package |
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self.image = Image.open(self.filedialog.askopenfilename(filetypes=[("Image Files", "*.png;*.jpg;*.jpeg")])) |
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@ -76,7 +110,7 @@ class ParkingPtsSelection: |
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self.rg_data.clear(), self.current_box.clear() |
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def on_canvas_click(self, event): |
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"""Handles mouse clicks to add points for bounding boxes.""" |
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"""Handles mouse clicks to add points for bounding boxes on the canvas.""" |
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self.current_box.append((event.x, event.y)) |
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self.canvas.create_oval(event.x - 3, event.y - 3, event.x + 3, event.y + 3, fill="red") |
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if len(self.current_box) == 4: |
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@ -85,12 +119,12 @@ class ParkingPtsSelection: |
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self.current_box.clear() |
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def draw_box(self, box): |
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"""Draws a bounding box on the canvas.""" |
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"""Draws a bounding box on the canvas using the provided coordinates.""" |
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for i in range(4): |
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self.canvas.create_line(box[i], box[(i + 1) % 4], fill="blue", width=2) |
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def remove_last_bounding_box(self): |
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"""Removes the last bounding box and redraws the canvas.""" |
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"""Removes the last bounding box from the list and redraws the canvas.""" |
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if not self.rg_data: |
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self.messagebox.showwarning("Warning", "No bounding boxes to remove.") |
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return |
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@ -105,7 +139,7 @@ class ParkingPtsSelection: |
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self.draw_box(box) |
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def save_to_json(self): |
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"""Saves the bounding boxes to a JSON file.""" |
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"""Saves the selected parking zone points to a JSON file with scaled coordinates.""" |
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scale_w, scale_h = self.imgw / self.canvas.winfo_width(), self.imgh / self.canvas.winfo_height() |
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data = [{"points": [(int(x * scale_w), int(y * scale_h)) for x, y in box]} for box in self.rg_data] |
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with open("bounding_boxes.json", "w") as f: |
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@ -114,7 +148,30 @@ class ParkingPtsSelection: |
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class ParkingManagement(BaseSolution): |
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"""Manages parking occupancy and availability using YOLO model for real-time monitoring and visualization.""" |
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""" |
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Manages parking occupancy and availability using YOLO model for real-time monitoring and visualization. |
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This class extends BaseSolution to provide functionality for parking lot management, including detection of |
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occupied spaces, visualization of parking regions, and display of occupancy statistics. |
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Attributes: |
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json_file (str): Path to the JSON file containing parking region details. |
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json (List[Dict]): Loaded JSON data containing parking region information. |
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pr_info (Dict[str, int]): Dictionary storing parking information (Occupancy and Available spaces). |
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arc (Tuple[int, int, int]): RGB color tuple for available region visualization. |
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occ (Tuple[int, int, int]): RGB color tuple for occupied region visualization. |
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dc (Tuple[int, int, int]): RGB color tuple for centroid visualization of detected objects. |
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Methods: |
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process_data: Processes model data for parking lot management and visualization. |
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Examples: |
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>>> from ultralytics.solutions import ParkingManagement |
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>>> parking_manager = ParkingManagement(model="yolov8n.pt", json_file="parking_regions.json") |
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>>> results = parking_manager(source="parking_lot_video.mp4") |
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>>> print(f"Occupied spaces: {parking_manager.pr_info['Occupancy']}") |
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>>> print(f"Available spaces: {parking_manager.pr_info['Available']}") |
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""" |
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def __init__(self, **kwargs): |
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"""Initializes the parking management system with a YOLO model and visualization settings.""" |
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@ -136,10 +193,19 @@ class ParkingManagement(BaseSolution): |
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def process_data(self, im0): |
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""" |
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Process the model data for parking lot management. |
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Processes the model data for parking lot management. |
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This function analyzes the input image, extracts tracks, and determines the occupancy status of parking |
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regions defined in the JSON file. It annotates the image with occupied and available parking spots, |
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and updates the parking information. |
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Args: |
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im0 (ndarray): inference image. |
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im0 (np.ndarray): The input inference image. |
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Examples: |
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>>> parking_manager = ParkingManagement(json_file="parking_regions.json") |
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>>> image = cv2.imread("parking_lot.jpg") |
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>>> parking_manager.process_data(image) |
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""" |
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self.extract_tracks(im0) # extract tracks from im0 |
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es, fs = len(self.json), 0 # empty slots, filled slots |
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Glenn Jocher
1 month ago
committed by
GitHub