dynamic dir changes and no need to use path.txt no more, added new folder to gitignore

.gitignore

@@ -6,7 +6,7 @@ data/matbase/masks/*
 
 # intermediate files
 output/
-split_output/
+cubemap_faces/
 
 # Byte-compiled / optimized / DLL files
 __pycache__/

combine_img.py

 import numpy as np
 import imageio
 import os
+import sys
 from ui import get_res
 
 #makes sure value of x stays within the range of min and max value to prevent out of bound values accses for the image
@@ -9,29 +10,11 @@ def clamp(x, min_val, max_val):
 
 #clamps the floating point coordinates to nearest integer value, copies pixel value from the image to the nearest int coord
 def nearest_neighbour_interpolation(img, x, y):
-    h, w, _ = img.shape
+    # Modified to handle both 2D and 3D images
+    h, w = img.shape[:2]
     x, y = clamp(int(x), 0, w-1), clamp(int(y), 0, h-1)
     return img[y, x]
 
-
-# def orientation_to_face(x, y, z):
-#     abs_x, abs_y, abs_z = abs(x), abs(y), abs(z)
-#     if abs_x >= abs_y and abs_x >= abs_z:
-#         if x > 0:
-#             return 'front', -y / abs_x, -z / abs_x
-#         else:
-#             return 'back', y / abs_x, -z / abs_x
-#     elif abs_y >= abs_x and abs_y >= abs_z:
-#         if y > 0:
-#             return 'right', -x / abs_y, -z / abs_y
-#         else:
-#             return 'left', x / abs_y, -z / abs_y
-#     else:
-#         if z > 0:
-#             return 'top', x / abs_z, y / abs_z
-#         else:
-#             return 'bottom', -x / abs_z, y / abs_z
-
 #maps the 3d coords for cube faces to 2d coords on that cube face
 #finds out which cube face corresponds to the current pixel for which the 3d coords are calculated and calcs the normalised 2d coords on that face
 def orientation_to_face(x, y, z):
@@ -54,6 +37,13 @@ def orientation_to_face(x, y, z):
 
 #converts cube maps into omnidirectional image
 def cubemap_to_omnidirectional(cube_faces, out_width, out_height):
+    # Determine if the input is grayscale or RGB
+    is_grayscale = len(cube_faces[list(cube_faces.keys())[0]].shape) == 2
+    
+    # Create the appropriate output array based on input type
+    if is_grayscale:
+        omnidirectional = np.zeros((out_height, out_width), dtype=np.uint8)
+    else:
         omnidirectional = np.zeros((out_height, out_width, 3), dtype=np.uint8)
     
     #iterates through the pixels in o/p image, for each pixel calulates spherical coord used to map 2d pixel loc to 3d points on a sphere
@@ -79,23 +69,27 @@ def cubemap_to_omnidirectional(cube_faces, out_width, out_height):
     
     return omnidirectional
 
-# if __name__ == "__main__":
-#     # Load the cubemap images
-#     cube_faces_dir = input("Enter the directory containing the cubemap images: ").strip()
-#     faces = ["right", "left", "top", "bottom", "front", "back"]
-#     cube_faces = {}
-    
-#     for face in faces:
-#         cube_faces[face] = imageio.imread(os.path.join(cube_faces_dir, f"{face}.jpg"))
-
+if __name__ == "__main__":
+    # Get the directory of the current script
+    script_dir = os.path.dirname(os.path.abspath(__file__))
+
+    # Default paths relative to the script directory
+    default_cube_faces_dir = os.path.join(script_dir, "output", "cubemap_faces")
+    default_output_dir = os.path.join(script_dir, "..", "edgenet-360", "Data", "Input")
+    rgb_png_path = os.path.join(script_dir, "..", "scripts", "360monodepthexecution", "rgb.jpg")
+
+    # Use command-line arguments for custom paths if provided
+    if len(sys.argv) > 2:
+        cube_faces_dir = sys.argv[1]
+        output_dir = sys.argv[2]
+    else:
+        cube_faces_dir = default_cube_faces_dir
+        output_dir = default_output_dir
 
+    # Ensure output directory exists
+    os.makedirs(output_dir, exist_ok=True)
 
-if __name__ == "__main__":
     # Load the cubemap images
-    #cube_faces_dir = input("Enter the directory containing the cubemap images: ").strip()
-    cube_faces_dir = "C:\Project\AVVR-Pipeline-Internship\material_recognition\Dynamic-Backward-Attention-Transformer\output\split_output"
-
-    #faces = ["right", "left", "top", "bottom", "front", "back"]
     faces = ["rightrgb", "leftrgb", "toprgb", "bottomrgb", "frontrgb", "backrgb"]
     cube_faces = {}
     
@@ -103,39 +97,23 @@ if __name__ == "__main__":
         image_path = os.path.join(cube_faces_dir, f"{face}.png")
         image_data = imageio.imread(image_path)
         
-        #rotate top and bottom face by 90 deg
-        # if face in ["top", "bottom"]:
-        #     image_data = np.rot90(image_data, 1)
-        
-        # #flip the top, bottom, front and back faces in horizontal direction
-        # if face not in ["left", "right"]:
-        #     image_data = image_data[:, ::-1]
-
         if face in ["toprgb", "bottomrgb"]:
             image_data = np.rot90(image_data, 1)
         
         if face not in ["leftrgb", "rightrgb"]:
             image_data = image_data[:, ::-1]
         
-        
         cube_faces[face] = image_data
 
-    
-    # output_width = int(input("Enter output omnidirectional width: "))
-    # output_height = int(input("Enter output omnidirectional height: "))
-    with open('path.txt', 'r') as file:
-        input_path = file.readline()
-        print(f'path = {input_path}')
-    os.remove('path.txt')
-    height, width = get_res(input_path)
-    print(height, width)
+    # Use the rgb.png file from edgenet-360 folder for dimensions
+    height, width = get_res(rgb_png_path)
+    print(f"Using dimensions from {rgb_png_path}: {width}x{height}")
     
     output_width = width
     output_height = height
 
-    #print(f"height: {height}, width: {width}")
     omnidirectional_img = cubemap_to_omnidirectional(cube_faces, output_width, output_height)
     
-    output_path = "C:\Project\AVVR-Pipeline-Internship\edgenet360\Data\Input\material.png"
+    output_path = os.path.join(output_dir, "material.png")
     imageio.v2.imsave(output_path, omnidirectional_img)
     print(f"Omnidirectional image saved to {output_path}")

split_img.py

 ###### This code has been Referenced from: https://github.com/jaxry/panorama-to-cubemap/blob/gh-pages/convert.js
 
-
 import numpy as np
 import imageio
 import os
@@ -16,7 +15,7 @@ def mod(x, n):
     return ((x % n) + n) % n
 
 #clamps the floating point coordinates to nearest integer value, copies pixel value from the image to the nearest int coord
-def nearest_neigbour_interpolation(img, x, y):
+def nearest_neighbour_interpolation(img, x, y):
     h, w, _ = img.shape
     x, y = clamp(int(x), 0, w-1), clamp(int(y), 0, h-1)
     return img[y, x]
@@ -49,56 +48,45 @@ def face_rendering(img, face, face_size):
             longitude = mod(np.arctan2(out[1], out[0]), 2 * np.pi)
             latitude = np.arccos(out[2] / r)
             s_x, s_y = img.shape[1] * longitude / (2 * np.pi) - 0.5, img.shape[0] * latitude / np.pi - 0.5
-            out_face[y, x] = nearest_neigbour_interpolation(img, s_x, s_y)
+            out_face[y, x] = nearest_neighbour_interpolation(img, s_x, s_y)
     return out_face
 
 #generates 6 cube faces
-def generate_cube_faces(input_path, output_path="cube_faces_output"):
-    
+def generate_cube_faces(input_path, output_path):
     img = imageio.imread(input_path)
 
     face_size = 512  #each face o/p image will be 512x512
     faces = ["right", "left", "top", "bottom", "front", "back"]
     
-    results = {}
     for face in faces:
-        results[face] = face_rendering(img, face, face_size)
+        face_img = face_rendering(img, face, face_size)
         face_output_path = os.path.join(output_path, f"{face}.png")
-        imageio.imsave(face_output_path, results[face])
+        imageio.imsave(face_output_path, face_img)
         print(f"Saved {face} face to {face_output_path}")
 
 
+if __name__ == "__main__":
+    # Get the directory of the current script
+    script_dir = os.path.dirname(os.path.abspath(__file__))
 
+    # Default output path relative to the script directory
+    default_output_path = os.path.join(script_dir, "cubemap_faces")
 
-# if __name__ == "__main__":
-#     input_path = select_image()
-#     height, width = get_res(input_path)
-#     print("width: , Height:", width, height)
-#     #output_path = input("Enter output directory: ").strip()
-#     #if not output_path:
-#     output_path = "C:\Project\AVVR-Pipeline-Internship\material_recognition\Dynamic-Backward-Attention-Transformer\split_output"
-#     if not os.path.exists(output_path):
-#         os.makedirs(output_path)
-#     generate_cube_faces(input_path, output_path)
-        
-
-#input_path = select_image()
+    # Use command-line arguments if provided
+    if len(sys.argv) > 1:
         input_path = sys.argv[1]
-with open('path.txt', 'w') as file:
-    file.write(input_path)
-    file.close()
-
-#output_path = input("Enter output directory: ").strip()
-#if not output_path:
-output_path = "C:\Project\AVVR-Pipeline-Internship\material_recognition\Dynamic-Backward-Attention-Transformer\split_output"
-if not os.path.exists(output_path):
-    os.makedirs(output_path)
+        if len(sys.argv) > 2:
+            output_path = sys.argv[2]
+        else:
+            output_path = default_output_path
+    else:
+        input_path = select_image()
+        output_path = default_output_path
+
+    # Ensure output directory exists
+    os.makedirs(output_path, exist_ok=True)
+
+    # Generate cube faces
     generate_cube_faces(input_path, output_path)
 
-
-
+    print(f"Cubemap faces saved to: {output_path}")
\ No newline at end of file
-
-
-
-
-

ui.py

 import tkinter as tk
 from tkinter import filedialog
 import cv2
+import os
 
 def select_image():
-    
     root = tk.Tk()
     root.withdraw() 
     
@@ -16,7 +16,15 @@ def select_image():
 def get_res(path):
     img = cv2.imread(path)
     height, width, _ = img.shape
-    cv2.imwrite('C:\Project\AVVR-Pipeline-Internship\edgenet360\Data\Input\\rgb.png', img)
+    
+    # Construct the output path dynamically
+    script_dir = os.path.dirname(os.path.abspath(__file__))
+    output_dir = os.path.join(script_dir, "..", "edgenet-360", "Data", "Input")
+    os.makedirs(output_dir, exist_ok=True)
+    output_path = os.path.join(output_dir, "rgb.png")
+    
+    cv2.imwrite(output_path, img)
+    print(f"RGB image saved to: {output_path}")
 
     return height, width