Build an image labeling app with Python

Creating an image labeling app with Python involves building a simple GUI (Graphical User Interface) that allows users to load images, annotate them (e.g., with bounding boxes or labels), and save the annotations. Below is a complete guide using Tkinter for the GUI and Pillow for image handling.

Dependencies

Install required packages:

bash
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pip install pillow

Image Labeling App with Tkinter

python
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import tkinter as tk
from tkinter import filedialog, messagebox
from PIL import Image, ImageTk
import os
import json

class ImageLabelingApp:
    def __init__(self, root):
        self.root = root
        self.root.title("Image Labeling App")

        self.image_panel = tk.Label(self.root)
        self.image_panel.pack()

        self.control_frame = tk.Frame(self.root)
        self.control_frame.pack()

        tk.Button(self.control_frame, text="Load Image", command=self.load_image).pack(side=tk.LEFT)
        tk.Button(self.control_frame, text="Next", command=self.next_image).pack(side=tk.LEFT)
        tk.Button(self.control_frame, text="Save Label", command=self.save_label).pack(side=tk.LEFT)

        self.label_entry = tk.Entry(self.control_frame)
        self.label_entry.pack(side=tk.LEFT)
        self.label_entry.insert(0, "Enter label")

        self.canvas = tk.Canvas(self.root, cursor="cross")
        self.canvas.pack()
        self.canvas.bind("<Button-1>", self.on_click)

        self.images = []
        self.image_index = 0
        self.labels = {}
        self.current_image_path = ""
        self.rect_start = None
        self.rect = None

    def load_image(self):
        directory = filedialog.askdirectory(title="Select Image Folder")
        if directory:
            self.images = [os.path.join(directory, f) for f in os.listdir(directory) if f.lower().endswith(('.png', '.jpg', '.jpeg'))]
            self.image_index = 0
            self.labels = {}
            self.load_current_image()

    def load_current_image(self):
        if self.image_index < len(self.images):
            self.current_image_path = self.images[self.image_index]
            img = Image.open(self.current_image_path)
            self.tk_img = ImageTk.PhotoImage(img)
            self.canvas.config(width=self.tk_img.width(), height=self.tk_img.height())
            self.canvas.create_image(0, 0, anchor="nw", image=self.tk_img)
            self.rect_start = None
            self.rect = None
        else:
            messagebox.showinfo("Done", "No more images.")

    def next_image(self):
        self.image_index += 1
        self.load_current_image()

    def on_click(self, event):
        if not self.rect_start:
            self.rect_start = (event.x, event.y)
        else:
            x0, y0 = self.rect_start
            x1, y1 = event.x, event.y
            label = self.label_entry.get()
            if self.current_image_path not in self.labels:
                self.labels[self.current_image_path] = []
            self.labels[self.current_image_path].append({
                "label": label,
                "box": [x0, y0, x1, y1]
            })
            self.canvas.create_rectangle(x0, y0, x1, y1, outline="red")
            self.rect_start = None

    def save_label(self):
        if not self.labels:
            messagebox.showwarning("No Data", "No labels to save.")
            return
        save_path = filedialog.asksaveasfilename(defaultextension=".json", filetypes=[("JSON files", "*.json")])
        if save_path:
            with open(save_path, "w") as f:
                json.dump(self.labels, f, indent=4)
            messagebox.showinfo("Saved", f"Labels saved to {save_path}")

if __name__ == "__main__":
    root = tk.Tk()
    app = ImageLabelingApp(root)
    root.mainloop()

Features

• Load all images from a folder.

• Click twice to draw bounding boxes.

• Assign a label using a text entry.

• Save all labeled data as a JSON file with the format:

json
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{
  "image1.jpg": [
    {
      "label": "cat",
      "box": [x0, y0, x1, y1]
    }
  ]
}

Optional Enhancements

• Add support for multi-label annotations per image.

• Implement undo for last rectangle.

• Display existing labels when reloading.

• Use more advanced libraries like OpenCV for higher performance or more complex GUIs with PyQt or Kivy.

This script provides a minimal, functional image annotation tool that you can easily customize for datasets or machine learning purposes.