G11-2025-Final Project

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h1. Codes

h2. gui.py

<pre><code class="python">

# gui.py

import tkinter as tk

from tkinter import ttk, filedialog, messagebox

import threading

import json

import os

# Import the logic classes

from main_alpha_blender import MainAlphaBlender

from video_processor import VideoProcessor

class BlenderGUI:

    """A Tkinter GUI with tabs for image and video edge blending."""

    def __init__(self, master):

        self.master = master

        master.title("Image and Video Edge Blender")

        master.geometry("600x450") # Increased height for new buttons

        # --- Create a Tabbed Interface ---

        self.notebook = ttk.Notebook(master)

        self.notebook.pack(pady=10, padx=10, fill="both", expand=True)

        self.image_tab = ttk.Frame(self.notebook, padding="10")

        self.video_tab = ttk.Frame(self.notebook, padding="10")

        self.notebook.add(self.image_tab, text="Image Blender")

        self.notebook.add(self.video_tab, text="Video Processor")

        # --- Populate each tab ---

        self.create_image_widgets()

        self.create_video_widgets()

        # --- NEW: Add a frame at the bottom for config management ---

        self.config_frame = ttk.Frame(master, padding=(10, 0, 10, 10))

        self.config_frame.pack(fill=tk.X, side=tk.BOTTOM)

        self.create_config_widgets()

        # --- NEW: Load default config on startup ---

        # It will silently fail if config.json doesn't exist, using hardcoded defaults.

        self.load_config(filepath="config.json", silent=True)

    def create_image_widgets(self):

        """Creates all widgets for the Image Blender tab."""

        self.image_blender = MainAlphaBlender()

        ttk.Label(self.image_tab, text="Input Image Directory:").grid(row=0, column=0, sticky=tk.W, pady=2)

        self.img_input_path_var = tk.StringVar(value=self.image_blender.image_path)

        ttk.Entry(self.image_tab, textvariable=self.img_input_path_var, width=50).grid(row=0, column=1, sticky=tk.EW, padx=5)

        ttk.Button(self.image_tab, text="Browse...", command=self.select_img_input_dir).grid(row=0, column=2)

        ttk.Label(self.image_tab, text="Output Directory:").grid(row=1, column=0, sticky=tk.W, pady=2)

        self.img_output_path_var = tk.StringVar(value=self.image_blender.output_dir)

        ttk.Entry(self.image_tab, textvariable=self.img_output_path_var, width=50).grid(row=1, column=1, sticky=tk.EW, padx=5)

        ttk.Button(self.image_tab, text="Browse...", command=self.select_img_output_dir).grid(row=1, column=2)

        ttk.Label(self.image_tab, text="Blend Width (pixels):").grid(row=2, column=0, sticky=tk.W, pady=5)

        self.img_blend_width_var = tk.IntVar(value=self.image_blender.blend_width)

        ttk.Entry(self.image_tab, textvariable=self.img_blend_width_var, width=10).grid(row=2, column=1, sticky=tk.W, padx=5)

        ttk.Label(self.image_tab, text="Gamma Value:").grid(row=3, column=0, sticky=tk.W, pady=2)

        self.img_gamma_var = tk.DoubleVar(value=self.image_blender.gamma_value)

        ttk.Entry(self.image_tab, textvariable=self.img_gamma_var, width=10).grid(row=3, column=1, sticky=tk.W, padx=5)

        ttk.Label(self.image_tab, text="Blend Method:").grid(row=4, column=0, sticky=tk.W, pady=2)

        self.img_method_var = tk.StringVar(value=self.image_blender.method)

        methods = ['linear', 'cosine', 'quadratic', 'sqrt', 'log', 'sigmoid']

        ttk.Combobox(self.image_tab, textvariable=self.img_method_var, values=methods, state="readonly").grid(row=4, column=1, sticky=tk.W, padx=5)

        self.img_preview_var = tk.BooleanVar(value=self.image_blender.preview)

        ttk.Checkbutton(self.image_tab, text="Show Preview After Processing", variable=self.img_preview_var).grid(row=5, column=1, sticky=tk.W, pady=10, padx=5)

        ttk.Button(self.image_tab, text="Run Blending Process", command=self.run_image_blending).grid(row=6, column=1, pady=20, sticky=tk.W)

        self.img_status_var = tk.StringVar(value="Ready.")

        ttk.Label(self.image_tab, textvariable=self.img_status_var, font=("Helvetica", 10, "italic")).grid(row=7, column=0, columnspan=3, sticky=tk.W, pady=5)

        self.image_tab.columnconfigure(1, weight=1)

    def create_video_widgets(self):

        """Creates all widgets for the Video Processor tab."""

        self.video_processor = VideoProcessor()

        ttk.Label(self.video_tab, text="Input Video File:").grid(row=0, column=0, sticky=tk.W, pady=2)

        self.vid_input_path_var = tk.StringVar()

        ttk.Entry(self.video_tab, textvariable=self.vid_input_path_var, width=50).grid(row=0, column=1, sticky=tk.EW, padx=5)

        ttk.Button(self.video_tab, text="Browse...", command=self.select_vid_input_file).grid(row=0, column=2)

        ttk.Label(self.video_tab, text="Output Directory:").grid(row=1, column=0, sticky=tk.W, pady=2)

        self.vid_output_path_var = tk.StringVar(value=self.video_processor.output_dir)

        ttk.Entry(self.video_tab, textvariable=self.vid_output_path_var, width=50).grid(row=1, column=1, sticky=tk.EW, padx=5)

        ttk.Button(self.video_tab, text="Browse...", command=self.select_vid_output_dir).grid(row=1, column=2)

        ttk.Label(self.video_tab, text="Blend Width (pixels):").grid(row=2, column=0, sticky=tk.W, pady=5)

        self.vid_blend_width_var = tk.IntVar(value=self.video_processor.blend_width)

        ttk.Entry(self.video_tab, textvariable=self.vid_blend_width_var, width=10).grid(row=2, column=1, sticky=tk.W, padx=5)

        ttk.Label(self.video_tab, text="Blend Method:").grid(row=3, column=0, sticky=tk.W, pady=2)

        self.vid_method_var = tk.StringVar(value=self.video_processor.blend_method)

        methods = ['linear', 'cosine']

        ttk.Combobox(self.video_tab, textvariable=self.vid_method_var, values=methods, state="readonly").grid(row=3, column=1, sticky=tk.W, padx=5)

        self.run_video_button = ttk.Button(self.video_tab, text="Process Video", command=self.run_video_processing_thread)

        self.run_video_button.grid(row=4, column=1, pady=20, sticky=tk.W)

        self.vid_status_var = tk.StringVar(value="Ready.")

        ttk.Label(self.video_tab, textvariable=self.vid_status_var).grid(row=5, column=0, columnspan=3, sticky=tk.W, pady=5)

        self.video_tab.columnconfigure(1, weight=1)

    def create_config_widgets(self):

        """Creates the Load and Save configuration buttons."""

        ttk.Button(self.config_frame, text="Load Config", command=self.load_config).pack(side=tk.LEFT, padx=5)

        ttk.Button(self.config_frame, text="Save Config", command=self.save_config).pack(side=tk.LEFT, padx=5)

    def load_config(self, filepath=None, silent=False):

        """Loads settings from a JSON file and updates the GUI."""

        if filepath is None:

            filepath = filedialog.askopenfilename(

                title="Open Configuration File",

                filetypes=[("JSON files", "*.json"), ("All files", "*.*")]

            )

        if not filepath or not os.path.exists(filepath):

            if not silent:

                messagebox.showwarning("Load Config", "No configuration file selected or file not found.")

            return

        try:

            with open(filepath, 'r') as f:

                data = json.load(f)

            # Update Image Tab variables

            self.img_input_path_var.set(data.get("image_path", "OriginalImages"))

            self.img_output_path_var.set(data.get("output_dir", "Results"))

            self.img_blend_width_var.set(data.get("blend_width", 200))

            self.img_gamma_var.set(data.get("gamma_value", 1.4))

            self.img_method_var.set(data.get("blend_method", "cosine"))

            self.img_preview_var.set(data.get("preview", True))

            # Update Video Tab variables

            self.vid_input_path_var.set(data.get("video_input_path", ""))

            self.vid_output_path_var.set(data.get("video_output_dir", "VideoResults"))

            self.vid_blend_width_var.set(data.get("video_blend_width", 100))

            self.vid_method_var.set(data.get("video_blend_method", "linear"))

            if not silent:

                messagebox.showinfo("Load Config", f"Configuration loaded successfully from {os.path.basename(filepath)}.")

        except Exception as e:

            if not silent:

                messagebox.showerror("Load Config Error", f"Failed to load or parse the configuration file.\n\nError: {e}")

    def save_config(self):

        """Saves the current GUI settings to a JSON file."""

        filepath = filedialog.asksaveasfilename(

            title="Save Configuration File",

            defaultextension=".json",

            initialfile="config.json",

            filetypes=[("JSON files", "*.json"), ("All files", "*.*")]

        )

        if not filepath:

            return

        try:

            config_data = {

                # Image Tab settings

                "image_path": self.img_input_path_var.get(),

                "output_dir": self.img_output_path_var.get(),

                "blend_width": self.img_blend_width_var.get(),

                "gamma_value": self.img_gamma_var.get(),

                "blend_method": self.img_method_var.get(),

                "preview": self.img_preview_var.get(),

                # Video Tab settings

                "video_input_path": self.vid_input_path_var.get(),

                "video_output_dir": self.vid_output_path_var.get(),

                "video_blend_width": self.vid_blend_width_var.get(),

                "video_blend_method": self.vid_method_var.get()

            }

            with open(filepath, 'w') as f:

                json.dump(config_data, f, indent=4)

            messagebox.showinfo("Save Config", f"Configuration saved successfully to {os.path.basename(filepath)}.")

        except Exception as e:

            messagebox.showerror("Save Config Error", f"Failed to save the configuration file.\n\nError: {e}")

    # --- Callbacks for Image Tab ---

    def select_img_input_dir(self):

        path = filedialog.askdirectory(title="Select Input Image Directory")

        if path: self.img_input_path_var.set(path)

    def select_img_output_dir(self):

        path = filedialog.askdirectory(title="Select Output Directory")

        if path: self.img_output_path_var.set(path)

    def run_image_blending(self):

        self.image_blender.image_path = self.img_input_path_var.get()

        self.image_blender.output_dir = self.img_output_path_var.get()

        self.image_blender.blend_width = self.img_blend_width_var.get()

        self.image_blender.gamma_value = self.img_gamma_var.get()

        self.image_blender.method = self.img_method_var.get()

        self.image_blender.preview = self.img_preview_var.get()

        self.image_blender.update_paths()

        success, message = self.image_blender.run()

        if success:

            self.img_status_var.set(f"Success! {message}")

            messagebox.showinfo("Success", message)

        else:

            self.img_status_var.set(f"Error: {message}")

            messagebox.showerror("Error", message)

    # --- Callbacks for Video Tab ---

    def select_vid_input_file(self):

        path = filedialog.askopenfilename(title="Select Input Video File", filetypes=[("MP4 files", "*.mp4"), ("All files", "*.*")])

        if path: self.vid_input_path_var.set(path)

    def select_vid_output_dir(self):

        path = filedialog.askdirectory(title="Select Output Directory")

        if path: self.vid_output_path_var.set(path)

    def update_video_status(self, message):

        """Thread-safe method to update the GUI status label."""

        self.vid_status_var.set(message)

    def run_video_processing_thread(self):

        """Starts the video processing in a new thread to avoid freezing the GUI."""

        self.run_video_button.config(state="disabled")

        thread = threading.Thread(target=self.run_video_processing)

        thread.daemon = True

        thread.start()

    def run_video_processing(self):

        """The actual processing logic, run in the background thread."""

        try:

            self.video_processor.input_video_path = self.vid_input_path_var.get()

            self.video_processor.output_dir = self.vid_output_path_var.get()

            self.video_processor.blend_width = self.vid_blend_width_var.get()

            self.video_processor.blend_method = self.vid_method_var.get()

            success, message = self.video_processor.run(status_callback=self.update_video_status)

            if success:

                messagebox.showinfo("Success", message)

            else:

                messagebox.showerror("Error", message)

        except Exception as e:

            messagebox.showerror("Critical Error", f"An unexpected error occurred: {e}")

        finally:

            self.run_video_button.config(state="normal")

</code></pre>

h2. main_alpha_blender.py

<pre><code class="python">

#!/usr/bin/env python

# -*- coding: utf-8 -*-

import cv2

import numpy as np

import os

from config_reader import ConfigReader

class MainAlphaBlender(object):

    def __init__(self, config_path="config.json"):

        try:

            self.__config_reader = ConfigReader(config_path)

            self.blend_width = self.__config_reader.get_blend_width()

            self.gamma_value = self.__config_reader.get_gamma_value()

            self.method = self.__config_reader.get_blend_method()

            self.output_dir = self.__config_reader.get_output_dir()

            self.preview = self.__config_reader.get_preview()

            self.image_path = self.__config_reader.get_image_path()

        except FileNotFoundError:

            self.blend_width = 200

            self.gamma_value = 1.4

            self.method = "cosine"

            self.output_dir = "Results"

            self.preview = True

            self.image_path = "OriginalImages"

        self.update_paths()

    def update_paths(self):

        self.left_image_path = os.path.join(self.image_path, "Left.jpg")

        self.right_image_path = os.path.join(self.image_path, "Right.jpg")

    def create_alpha_gradient(self, blend_width, side, method="cosine"):

        if method == 'linear':

            alpha_gradient = np.linspace(0, 1, blend_width)

        elif method == 'cosine':

            t = np.linspace(0, np.pi, blend_width)

            alpha_gradient = (1 - np.cos(t**0.85)) / 2

        elif method == 'quadratic':

            t = np.linspace(0, 1, blend_width)

            alpha_gradient = t**2

        elif method == 'sqrt':

            t = np.linspace(0, 1, blend_width)

            alpha_gradient = np.sqrt(t)

        elif method == 'log':

            t = np.linspace(0, 1, blend_width)

            alpha_gradient = np.log1p(9 * t) / np.log1p(9)

        elif method == 'sigmoid':

            t = np.linspace(0, 1, blend_width)

            alpha_gradient = 1 / (1 + np.exp(-12 * (t - 0.5)))

            alpha_gradient = (alpha_gradient - alpha_gradient.min()) / (alpha_gradient.max() - alpha_gradient.min())

        else:

            raise ValueError("Invalid method: choose from 'linear', 'cosine', 'quadratic', 'sqrt', 'log', or 'sigmoid'")

        if side == 'right':

            alpha_gradient = 1 - alpha_gradient

        return alpha_gradient

    def gamma_correction(self, image, gamma):

        img_float = image.astype(np.float32) / 255.0

        mean_intensity = np.mean(img_float)

        adaptive_gamma = gamma * (0.5 / (mean_intensity + 1e-5))

        adaptive_gamma = np.clip(adaptive_gamma, 0.8, 2.0)

        corrected = np.power(img_float, 1.0 / adaptive_gamma)

        return np.uint8(np.clip(corrected * 255, 0, 255))

    def alpha_blend_edge(self, image, blend_width, side, method="cosine"):

        height, width, _ = image.shape

        blended_image = image.copy()

        alpha_gradient = self.create_alpha_gradient(blend_width, side, method)

        if side == 'right':

            roi = blended_image[:, width - blend_width:]

        elif side == 'left':

            roi = blended_image[:, :blend_width]

        else:

            raise ValueError("Side must be 'left' or 'right'")

        gradient_3d = alpha_gradient[np.newaxis, :, np.newaxis]

        gradient_3d = np.tile(gradient_3d, (height, 1, 3))

        if side == 'right':

            blended_image[:, width - blend_width:] = (roi * gradient_3d).astype(np.uint8)

        else:

            blended_image[:, :blend_width] = (roi * gradient_3d).astype(np.uint8)

        return blended_image

    def show_preview(self, left_image, right_image, scale=0.5):

        h = min(left_image.shape[0], right_image.shape[0])

        left_resized = cv2.resize(left_image, (int(left_image.shape[1]*scale), int(h*scale)))

        right_resized = cv2.resize(right_image, (int(right_image.shape[1]*scale), int(h*scale)))

        combined = np.hstack((left_resized, right_resized))

        cv2.imshow("Preview (Left + Right)", combined)

        cv2.waitKey(0)

        cv2.destroyAllWindows()

    def run(self):

        try:

            os.makedirs(self.output_dir, exist_ok=True)

            left_img = cv2.imread(self.left_image_path, cv2.IMREAD_COLOR)

            right_img = cv2.imread(self.right_image_path, cv2.IMREAD_COLOR)

            if left_img is None or right_img is None:

                raise FileNotFoundError(f"Could not read images from '{self.image_path}'. Check path.")

            left_blended = self.alpha_blend_edge(left_img, self.blend_width, side='right', method=self.method)

            right_blended = self.alpha_blend_edge(right_img, self.blend_width, side='left', method=self.method)

            left_gamma = self.gamma_correction(left_blended, self.gamma_value)

            right_gamma = self.gamma_correction(right_blended, self.gamma_value)

            left_output_path = os.path.join(self.output_dir, f"{self.method}_left_gamma.jpg")

            right_output_path = os.path.join(self.output_dir, f"{self.method}_right_gamma.jpg")

            cv2.imwrite(left_output_path, left_gamma)

            cv2.imwrite(right_output_path, right_gamma)

            if self.preview:

                self.show_preview(left_gamma, right_gamma)

            return (True, f"Images saved successfully in '{self.output_dir}'.")

        except (FileNotFoundError, ValueError) as e:

            return (False, str(e))

        except Exception as e:

            return (False, f"An unexpected error occurred: {e}")

        finally:

            cv2.destroyAllWindows()

</code></pre>

h2. main.py

<pre><code class="python">

import tkinter as tk

from gui import BlenderGUI

if __name__ == "__main__":

    """

    Main entry point for the application.

    Initializes and runs the Tkinter GUI.

    """

    root = tk.Tk()

    app = BlenderGUI(master=root)

    root.mainloop()

</code></pre>

h2. video_processor.py

<pre><code class="python">

import cv2

import numpy as np

import os

import time

class VideoProcessor:

    """

    A class to handle dividing a video and applying alpha blending to the edges.

    Consolidates logic from divide_video.py, apply_alpha_blending_on_video.py, and Video_utility.py.

    """

    def __init__(self, config=None):

        """Initializes the processor with default or provided settings."""

        # Set default parameters

        self.input_video_path = ""

        self.output_dir = "VideoResults"

        self.blend_width = 100

        self.blend_method = "linear"

        self.divide_ratio = 2/3

        # Overwrite defaults with a configuration dictionary if provided

        if config:

            self.input_video_path = config.get("input_video_path", self.input_video_path)

            self.output_dir = config.get("output_dir", self.output_dir)

            self.blend_width = config.get("blend_width", self.blend_width)

            self.blend_method = config.get("blend_method", self.blend_method)

            self.divide_ratio = config.get("divide_ratio", self.divide_ratio)

    def _create_alpha_gradient(self, blend_width, side, method):

        """Creates a 1D alpha gradient for blending."""

        if method == 'linear':

            alpha_gradient = np.linspace(0, 1, blend_width)

        elif method == 'cosine':

            t = np.linspace(0, np.pi, blend_width)

            alpha_gradient = (1 - np.cos(t)) / 2

        else:

            raise ValueError(f"Invalid blend method: {method}")

        if side == 'right':

            alpha_gradient = 1 - alpha_gradient  # Create a fade-out gradient

        return alpha_gradient

    def _blend_image_edge(self, image, blend_width, side, method):

        """Applies the alpha gradient to a single frame."""

        height, width, _ = image.shape

        blended_image = image.copy()

        alpha_gradient = self._create_alpha_gradient(blend_width, side, method)

        if side == 'right':

            roi = blended_image[:, width - blend_width:]

        elif side == 'left':

            roi = blended_image[:, :blend_width]

        else:

            raise ValueError("Side must be 'left' or 'right'")

        # Tile the 1D gradient to match the 3 color channels of the ROI

        gradient_3d = alpha_gradient[np.newaxis, :, np.newaxis]

        gradient_3d = np.tile(gradient_3d, (height, 1, 3))

        if side == 'right':

            blended_image[:, width - blend_width:] = (roi * gradient_3d).astype(np.uint8)

        else:

            blended_image[:, :blend_width] = (roi * gradient_3d).astype(np.uint8)

        return blended_image

    def _divide_video(self, input_path, output_left_path, output_right_path, status_callback):

        """Splits a video into two halves based on the divide_ratio."""

        cap = cv2.VideoCapture(input_path)

        if not cap.isOpened():

            raise FileNotFoundError(f"Could not open video file: {input_path}")

        fourcc = cv2.VideoWriter_fourcc(*'mp4v')

        fps = cap.get(cv2.CAP_PROP_FPS)

        width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))

        height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))

        midpoint = int(width * self.divide_ratio)

        out_left = cv2.VideoWriter(output_left_path, fourcc, fps, (midpoint, height))

        out_right = cv2.VideoWriter(output_right_path, fourcc, fps, (width - midpoint, height))

        total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))

        frame_count = 0

        while cap.isOpened():

            ret, frame = cap.read()

            if not ret: break

            frame_count += 1

            if status_callback and frame_count % 30 == 0: # Update status every 30 frames

                progress = int((frame_count / total_frames) * 100)

                status_callback(f"Dividing video... {progress}%")

            out_left.write(frame[:, :midpoint])

            out_right.write(frame[:, midpoint:])

        cap.release()

        out_left.release()

        out_right.release()

    def _apply_alpha_blending_to_video(self, input_path, output_path, side, status_callback):

        """Applies alpha blending to each frame of a video."""

        cap = cv2.VideoCapture(input_path)

        if not cap.isOpened(): raise FileNotFoundError(f"Could not open video for blending: {input_path}")

        fourcc = cv2.VideoWriter_fourcc(*'mp4v')

        fps = cap.get(cv2.CAP_PROP_FPS)

        width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))

        height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))

        out = cv2.VideoWriter(output_path, fourcc, fps, (width, height))

        total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))

        frame_count = 0

        while cap.isOpened():

            ret, frame = cap.read()

            if not ret: break

            frame_count += 1

            if status_callback and frame_count % 30 == 0:

                progress = int((frame_count / total_frames) * 100)

                status_callback(f"Blending {side} video... {progress}%")

            blended_frame = self._blend_image_edge(frame, self.blend_width, side, self.blend_method)

            out.write(blended_frame)

        cap.release()

        out.release()

    def run(self, status_callback=None):

        """Executes the full video processing pipeline."""

        try:

            start_time = time.time()

            os.makedirs(self.output_dir, exist_ok=True)

            # Define intermediate and final file paths

            temp_left_path = os.path.join(self.output_dir, "temp_left.mp4")

            temp_right_path = os.path.join(self.output_dir, "temp_right.mp4")

            final_left_path = os.path.join(self.output_dir, "final_left.mp4")

            final_right_path = os.path.join(self.output_dir, "final_right.mp4")

            if status_callback: status_callback("Starting to divide video...")

            self._divide_video(self.input_video_path, temp_left_path, temp_right_path, status_callback)

            if status_callback: status_callback("Starting to blend left video...")

            self._apply_alpha_blending_to_video(temp_left_path, final_left_path, "right", status_callback)

            if status_callback: status_callback("Starting to blend right video...")

            self._apply_alpha_blending_to_video(temp_right_path, final_right_path, "left", status_callback)

            if status_callback: status_callback("Cleaning up temporary files...")

            os.remove(temp_left_path)

            os.remove(temp_right_path)

            duration = time.time() - start_time

            message = f"Video processing complete in {duration:.2f}s. Files saved in '{self.output_dir}'."

            if status_callback: status_callback(message)

            return (True, message)

        except Exception as e:

            if status_callback: status_callback(f"Error: {e}")

            return (False, str(e))

</code></pre>

h2. config_reader.py

<pre><code class="python">

#!/usr/bin/env python

# -*- coding: utf-8 -*-

import json

class ConfigReader:

    """

    ConfigReader loads configuration settings from a JSON file.

    It now uses a single base path for input images.

    """

    def __init__(self, json_path: str):

        """

        Initialize the ConfigReader with the path to the configuration file.

        :param json_path: Path to the JSON configuration file

        """

        self.json_path = json_path

        self.config = None

        self.load_config()

    def load_config(self):

        """Load configuration data from the JSON file."""

        try:

            with open(self.json_path, 'r', encoding='utf-8') as f:

                self.config = json.load(f)

        except FileNotFoundError:

            raise FileNotFoundError(f"Configuration file not found: {self.json_path}")

        except json.JSONDecodeError as e:

            raise ValueError(f"Error decoding JSON: {e}")

    def get_blend_width(self) -> int:

        """Return the blending width."""

        return self.config.get("blend_width", 200)

    def get_gamma_value(self) -> float:

        """Return the gamma correction value."""

        return self.config.get("gamma_value", 1.0)

    def get_blend_method(self) -> str:

        """Return the blending method (e.g., 'cosine', 'linear')."""

        return self.config.get("blend_method", "linear")

    def get_image_path(self) -> str:

        """Return the base directory of the input images."""

        return self.config.get("image_path", "")

    def get_output_dir(self) -> str:

        """Return the directory for output results."""

        return self.config.get("output_dir", "Results")

    def get_preview(self) -> bool:

        """Return the preview flag."""

        return self.config.get("preview", False)

</code></pre>