Add option to toggle transparency processing

Introduced a `use_transparency` parameter to allow users to choose between RGBA (transparent) and RGB (opaque) processing modes via the UI.

app.py

@@ -1489,6 +1489,7 @@ def stitch_pairwise_images(img_composite, img_new,
 
 # --- Function for N-Image Stitching (Primarily for Image List Input) ---
 def stitch_multiple_images(images, # List of NumPy images (BGR/BGRA, potentially pre-cropped)
+                                    use_transparency=True,
                                     stitcher_mode_str="SCANS",
                                     registration_resol=0.6,
                                     seam_estimation_resol=0.1,
@@ -1509,14 +1510,15 @@ def stitch_multiple_images(images, # List of NumPy images (BGR/BGRA, potentially
                                     max_blending_height=10000,
                                     blend_smooth_ksize=15,
                                     num_blend_levels=4,
-                                    fixed_base_image_index=-1
+                                    fixed_base_image_index=-1,
                                     ):
     """
     Stitches a list of images. Tries cv2.Stitcher first (unless 'DIRECT_PAIRWISE'),
     otherwise falls back to manual pairwise stitching.
     Returns ONE stitched image (RGB/RGBA) and log.
-    Input images should be in BGR format (already potentially cropped by caller).
+    Input images should be in BGR or BGRA format (already potentially cropped by caller).
     Output is RGBA. The 'enable_cropping' param here refers to final black border cropping.
+    If use_transparency is False, the final output will be RGB (opaque background).
     """
     log = log_and_print(f"--- Starting Stitching Process for {len(images)} Provided Images ---\n", "")
     total_start_time = time.time()
@@ -1796,7 +1798,8 @@ def stitch_multiple_images(images, # List of NumPy images (BGR/BGRA, potentially
 
     # Clean up the input image list now that it's processed
     del images
-    if 'valid_images' in locals(): del valid_images # Should be same as images now
+    if 'valid_images' in locals():
+        del valid_images # Should be same as images now
     gc.collect()
 
     # 3. Final Result Check and Return (Handling Alpha Channel)
@@ -1806,15 +1809,26 @@ def stitch_multiple_images(images, # List of NumPy images (BGR/BGRA, potentially
     if stitched_img_bgra is not None and stitched_img_bgra.size > 0:
         log = log_and_print("Stitching process finished for image list.", log)
         try:
-            # Check channel count to preserve transparency
-            if stitched_img_bgra.shape[2] == 4:
+            # Handle final output based on transparency flag
+            if use_transparency:
+                # Preserve/Ensure RGBA
+                if stitched_img_bgra.shape[2] == 4:
                 # Convert BGRA to RGBA
-                stitched_img_rgba = cv2.cvtColor(stitched_img_bgra, cv2.COLOR_BGRA2RGBA)
-                log = log_and_print("Converted BGRA to RGBA (Transparency preserved).", log)
+                    stitched_img_rgba = cv2.cvtColor(stitched_img_bgra, cv2.COLOR_BGRA2RGBA)
+                    log = log_and_print("Converted BGRA to RGBA (Transparency preserved).", log)
+                else:
+                    # Source was BGR, make it RGBA (solid alpha)
+                    stitched_img_rgba = cv2.cvtColor(stitched_img_bgra, cv2.COLOR_BGR2RGBA)
+                    log = log_and_print("Converted BGR to RGBA.", log)
             else:
-                # Convert BGR to RGB
-                stitched_img_rgba = cv2.cvtColor(stitched_img_bgra, cv2.COLOR_BGR2RGB)
-                log = log_and_print("Converted BGR to RGB.", log)
+                # Force RGB (Drop Alpha / Opaque)
+                if stitched_img_bgra.shape[2] == 4:
+                    stitched_img_rgba = cv2.cvtColor(stitched_img_bgra, cv2.COLOR_BGRA2RGB)
+                    log = log_and_print("Converted BGRA to RGB (Transparency disabled, alpha dropped).", log)
+                else:
+                    # Convert BGR to RGB
+                    stitched_img_rgba = cv2.cvtColor(stitched_img_bgra, cv2.COLOR_BGR2RGB)
+                    log = log_and_print("Converted BGR to RGB.", log)
                 
             del stitched_img_bgra # Release BGRA version
             gc.collect()
@@ -1834,6 +1848,7 @@ def stitch_multiple_images(images, # List of NumPy images (BGR/BGRA, potentially
 
 # --- Video Frame Stitching ---
 def stitch_video_frames(video_path,
+                        use_transparency=True,
                         crop_top_percent=0.0,
                         crop_bottom_percent=0.0,
                         enable_cropping=True, # This is for POST-stitch cropping
@@ -1854,10 +1869,11 @@ def stitch_video_frames(video_path,
                         sample_interval_ms=3000,
                         max_composite_width=10000,
                         max_composite_height=10000,
-                        progress=None):
+                        progress=None,
+                        ):
     """
     Reads a video, samples frames, and stitches them sequentially.
-    Returns a list of stitched images (RGBA/RGB) and a log.
+    Returns a list of stitched images (RGBA if transparency=True, else RGB) and a log.
     """
     log = log_and_print(f"--- Starting Incremental Video Stitching: {os.path.basename(video_path)} ---\n", "")
     log = log_and_print(f"Params: Interval={sample_interval_ms}ms, Transform={transform_model_str}, ORB={orb_nfeatures}, Ratio={match_ratio_thresh}\n", log)
@@ -1867,7 +1883,7 @@ def stitch_video_frames(video_path,
     log = log_and_print(f"Post-Crop Black Borders: {enable_cropping}, Strict Edges: {strict_no_black_edges}\n", log)
     log = log_and_print(f"Blending: Method={blend_method}, GainComp={enable_gain_compensation}, SmoothKSize={blend_smooth_ksize}, MB Levels={num_blend_levels}\n", log)
     total_start_time = time.time()
-    stitched_results_rgba = [] # Store final RGBA images
+    stitched_results_rgba = [] # Store final images (RGBA or RGB)
 
     cap = cv2.VideoCapture(video_path)
     if not cap.isOpened():
@@ -1900,10 +1916,17 @@ def stitch_video_frames(video_path,
     # Helper to save image to results list with correct color conversion
     def append_result(img_bgr_or_bgra):
         try:
-            if img_bgr_or_bgra.shape[2] == 4:
-                stitched_results_rgba.append(cv2.cvtColor(img_bgr_or_bgra, cv2.COLOR_BGRA2RGBA))
+            if use_transparency:
+                if img_bgr_or_bgra.shape[2] == 4:
+                    stitched_results_rgba.append(cv2.cvtColor(img_bgr_or_bgra, cv2.COLOR_BGRA2RGBA))
+                else:
+                    stitched_results_rgba.append(cv2.cvtColor(img_bgr_or_bgra, cv2.COLOR_BGR2RGBA))
             else:
-                stitched_results_rgba.append(cv2.cvtColor(img_bgr_or_bgra, cv2.COLOR_BGR2RGB))
+                # Force RGB Output
+                if img_bgr_or_bgra.shape[2] == 4:
+                     stitched_results_rgba.append(cv2.cvtColor(img_bgr_or_bgra, cv2.COLOR_BGRA2RGB))
+                else:
+                     stitched_results_rgba.append(cv2.cvtColor(img_bgr_or_bgra, cv2.COLOR_BGR2RGB))
             return True
         except Exception as e:
             print(f"Error converting result: {e}")
@@ -1925,25 +1948,41 @@ def stitch_video_frames(video_path,
                 if frame_bgr_raw is not None and frame_bgr_raw.size > 0:
                     processed_sampled_count += 1
                     frame_bgra = None # Initialize BGR frame variable
-                
-                    # Ensure BGRA for processing
-                    if frame_bgr_raw.ndim == 2:
-                        frame_bgra = cv2.cvtColor(frame_bgr_raw, cv2.COLOR_GRAY2BGRA)
-                    elif frame_bgr_raw.ndim == 3 and frame_bgr_raw.shape[2] == 3:
-                        # Add alpha channel (opaque)
-                        frame_bgra = cv2.cvtColor(frame_bgr_raw, cv2.COLOR_BGR2BGRA)
-                    elif frame_bgr_raw.ndim == 3 and frame_bgr_raw.shape[2] == 4:
-                        frame_bgra = frame_bgr_raw
+
+                    # Handle Transparency Input
+                    if not use_transparency:
+                        # If transparency is disabled, ensure we treat the input as Opaque BGRA
+                        # We must use BGRA for the internal stitcher to work (warping masks), 
+                        # but we ensure the Alpha channel is full (255).
+                        if frame_bgr_raw.ndim == 3 and frame_bgr_raw.shape[2] == 3:
+                            frame_bgra = cv2.cvtColor(frame_bgr_raw, cv2.COLOR_BGR2BGRA)
+                        elif frame_bgr_raw.ndim == 3 and frame_bgr_raw.shape[2] == 4:
+                             # Drop existing alpha and replace with opaque
+                             temp_bgr = cv2.cvtColor(frame_bgr_raw, cv2.COLOR_BGRA2BGR)
+                             frame_bgra = cv2.cvtColor(temp_bgr, cv2.COLOR_BGR2BGRA)
+                             del temp_bgr
+                        else:
+                             # Grayscale
+                             frame_bgra = cv2.cvtColor(frame_bgr_raw, cv2.COLOR_GRAY2BGRA)
                     else:
-                        log = log_and_print(f"Warning: Skipping frame {frame_num} due to unexpected shape {frame_bgr_raw.shape}\n", log)
-                        if frame_bgr_raw is not None:
-                            del frame_bgr_raw # Clean up original frame
-                        gc.collect()
-                        frame_num += 1
-                        continue # Skip to next frame read
+                        # Standard Transparency Handling
+                        if frame_bgr_raw.ndim == 2:
+                            frame_bgra = cv2.cvtColor(frame_bgr_raw, cv2.COLOR_GRAY2BGRA)
+                        elif frame_bgr_raw.ndim == 3 and frame_bgr_raw.shape[2] == 3:
+                            # Add alpha channel (opaque)
+                            frame_bgra = cv2.cvtColor(frame_bgr_raw, cv2.COLOR_BGR2BGRA)
+                        elif frame_bgr_raw.ndim == 3 and frame_bgr_raw.shape[2] == 4:
+                            frame_bgra = frame_bgr_raw
+                        else:
+                            log = log_and_print(f"Warning: Skipping frame {frame_num} due to unexpected shape {frame_bgr_raw.shape}\n", log)
+                            if frame_bgr_raw is not None:
+                                del frame_bgr_raw # Clean up original frame
+                            gc.collect()
+                            frame_num += 1
+                            continue # Skip to next frame read
                     
                     # Release the raw frame once converted/checked (if a copy was made)
-                    if frame_bgra is not frame_bgr_raw:
+                    if frame_bgra is not frame_bgr_raw and frame_bgr_raw is not None:
                         del frame_bgr_raw
                         frame_bgr_raw = None # Mark as deleted
                         gc.collect()
@@ -2246,6 +2285,7 @@ def stitch_video_frames(video_path,
 
 # --- Gradio Interface Function ---
 def run_stitching_interface(input_files,
+    use_transparency,
     crop_top_percent,
     crop_bottom_percent,
     stitcher_mode_str, # For cv2.Stitcher
@@ -2413,6 +2453,7 @@ def run_stitching_interface(input_files,
 
         final_stitched_images_rgba, stitch_log = stitch_video_frames(
             video_path,
+            use_transparency=use_transparency,
             crop_top_percent=crop_top_percent,
             crop_bottom_percent=crop_bottom_percent,
             enable_cropping=enable_cropping, # Post-stitch crop
@@ -2445,11 +2486,16 @@ def run_stitching_interface(input_files,
             try:
                 n = np.fromfile(img_path, np.uint8)
                 if n.size > 0:
+                    # Load logic based on transparency flag
+                    if use_transparency:
                         # Use IMREAD_UNCHANGED to keep Alpha
                         img = cv2.imdecode(n, cv2.IMREAD_UNCHANGED)
+                    else:
+                        img = cv2.imdecode(n, cv2.IMREAD_COLOR) # Ignore alpha
                 else:
-                        log = log_and_print(f"Error: File is empty: {os.path.basename(img_path)}. Skipping.\n", log)
-                        continue
+                    log = log_and_print(f"Error: File is empty: {os.path.basename(img_path)}. Skipping.\n", log)
+                    continue
+
                 if img is None:
                          raise ValueError("imdecode returned None")
             except Exception as e_read:
@@ -2458,22 +2504,36 @@ def run_stitching_interface(input_files,
                     del img
                 continue # Skip to the next image
 
-            # Convert to BGRA for consistency
+            # Convert to BGRA for internal processing consistency
+            # (Internal stitching needs masks, so we use BGRA format even if opaque)
             img_bgra = None
             try:
-                if img.ndim == 2:
-                    img_bgra = cv2.cvtColor(img, cv2.COLOR_GRAY2BGRA)
-                elif img.ndim == 3 and img.shape[2] == 3:
-                    img_bgra = cv2.cvtColor(img, cv2.COLOR_BGR2BGRA)
-                elif img.ndim == 3 and img.shape[2] == 4:
-                    img_bgra = img # Already BGRA
+                if use_transparency:
+                    if img.ndim == 2:
+                        img_bgra = cv2.cvtColor(img, cv2.COLOR_GRAY2BGRA)
+                    elif img.ndim == 3 and img.shape[2] == 3:
+                        img_bgra = cv2.cvtColor(img, cv2.COLOR_BGR2BGRA)
+                    elif img.ndim == 3 and img.shape[2] == 4:
+                        img_bgra = img # Already BGRA
+                    else:
+                        log = log_and_print(f"Error: Invalid image shape {img.shape} for {os.path.basename(img_path)}. Skipping.\n", log)
+                        del img
+                        if 'img_bgra' in locals() and img_bgra is not None:
+                            del img_bgra
+                        gc.collect()
+                        continue # Skip to the next image
                 else:
-                    log = log_and_print(f"Error: Invalid image shape {img.shape} for {os.path.basename(img_path)}. Skipping.\n", log)
-                    del img
-                    if 'img_bgra' in locals() and img_bgra is not None:
-                        del img_bgra
-                    gc.collect()
-                    continue # Skip to the next image
+                    # Force Opaque BGRA
+                    if img.ndim == 2:
+                        img_bgra = cv2.cvtColor(img, cv2.COLOR_GRAY2BGRA)
+                    elif img.ndim == 3 and img.shape[2] == 3:
+                        img_bgra = cv2.cvtColor(img, cv2.COLOR_BGR2BGRA)
+                    elif img.ndim == 3 and img.shape[2] == 4: 
+                         # Drop alpha, re-add opaque
+                         tmp = cv2.cvtColor(img, cv2.COLOR_BGRA2BGR)
+                         img_bgra = cv2.cvtColor(tmp, cv2.COLOR_BGR2BGRA)
+                         del tmp
+
             except cv2.error as e_cvt_color:
                 log = log_and_print(f"Error converting image color for {os.path.basename(img_path)}: {e_cvt_color}. Skipping.\n", log)
                 del img
@@ -2516,7 +2576,8 @@ def run_stitching_interface(input_files,
 
             # Call the modified stitch_multiple_images function
         stitched_single_rgba, stitch_log_img = stitch_multiple_images(
-            images_bgr_cropped, # Pass the list of cropped images (BGRA)
+            images_bgr_cropped, # Pass the list of cropped images (BGRA/BGR)
+            use_transparency=use_transparency,
             stitcher_mode_str=stitcher_mode_str,
             registration_resol=registration_resol,
             seam_estimation_resol=seam_estimation_resol,
@@ -2618,12 +2679,19 @@ def run_stitching_interface(input_files,
                 full_path = os.path.join(temp_dir, filename)
                 img_bgra = None # Initialize for finally block
                 try:
-                    # Handle RGBA to BGRA for saving
-                    # The result coming from stitcher is in RGB(A) format
-                    if img_rgba.shape[2] == 4:
-                        img_bgra = cv2.cvtColor(img_rgba, cv2.COLOR_RGBA2BGRA)
+                    if use_transparency:
+                        # Handle RGBA to BGRA for saving
+                        # The result coming from stitcher is in RGB(A) format
+                        if img_rgba.shape[2] == 4:
+                            img_bgra = cv2.cvtColor(img_rgba, cv2.COLOR_RGBA2BGRA)
+                        else:
+                            img_bgra = cv2.cvtColor(img_rgba, cv2.COLOR_RGB2BGR)
                     else:
-                        img_bgra = cv2.cvtColor(img_rgba, cv2.COLOR_RGB2BGR)
+                        # Transparency Disabled: Output should be RGB (saved as BGR)
+                        if img_rgba.shape[2] == 4:
+                            img_bgra = cv2.cvtColor(img_rgba, cv2.COLOR_RGBA2BGR) # Drop Alpha
+                        else:
+                            img_bgra = cv2.cvtColor(img_rgba, cv2.COLOR_RGB2BGR)
                 
                     # Use imencode -> write pattern for better handling of paths/special chars
                     is_success, buf = cv2.imencode('.png', img_bgra)
@@ -2685,6 +2753,8 @@ with gr.Blocks() as demo:
 
             # --- Parameters Grouping ---
             with gr.Accordion("Preprocessing Settings", open=True):
+                use_transparency = gr.Checkbox(value=True, label="Use Transparency", 
+                    info="If Checked: Preserves alpha channel (RGBA). Unchecked: Treats images as opaque and outputs RGB (Black background for warped areas).")
                 crop_top_percent = gr.Slider(0.0, 49.0, step=0.5, value=0.0, label="Crop Top %",
                                                                          info="Percentage of height to remove from the TOP of each image/frame BEFORE stitching.")
                 crop_bottom_percent = gr.Slider(0.0, 49.0, step=0.5, value=0.0, label="Crop Bottom %",
@@ -2762,6 +2832,7 @@ with gr.Blocks() as demo:
         inputs=[
                 input_files,
                 # Preprocessing
+                use_transparency,
                 crop_top_percent,
                 crop_bottom_percent,
                 # OpenCV Stitcher (Image List)
@@ -2797,7 +2868,7 @@ with gr.Blocks() as demo:
         examples = [
         [
             ["examples/Wetter-Panorama/Wetter-Panorama1[NIuO6hrFTrg].mp4"],
-            0, 20,
+            True, 0, 20,
             "DIRECT_PAIRWISE", 0.6, 0.1, -1, False, "GAIN_BLOCKS",
             True, False, -1,
             "Homography", "Multi-Band", True, 5000, 0.5, 5.0, 0.5, 10000, 10000, 15, 4,
@@ -2805,7 +2876,7 @@ with gr.Blocks() as demo:
         ],
         [
             ["examples/Wetter-Panorama/Wetter-Panorama2[NIuO6hrFTrg].mp4"],
-            0, 20,
+            True, 0, 20,
             "DIRECT_PAIRWISE", 0.6, 0.1, -1, False, "GAIN_BLOCKS",
             True, False, -1,
             "Homography", "Multi-Band", True, 5000, 0.5, 5.0, 0.5, 10000, 10000, 15, 4,
@@ -2814,7 +2885,7 @@ with gr.Blocks() as demo:
         [
             ["examples/NieRAutomata/nier2B_01.jpg", "examples/NieRAutomata/nier2B_02.jpg", "examples/NieRAutomata/nier2B_03.jpg", "examples/NieRAutomata/nier2B_04.jpg", "examples/NieRAutomata/nier2B_05.jpg",
              "examples/NieRAutomata/nier2B_06.jpg", "examples/NieRAutomata/nier2B_07.jpg", "examples/NieRAutomata/nier2B_08.jpg", "examples/NieRAutomata/nier2B_09.jpg", "examples/NieRAutomata/nier2B_10.jpg", ],
-            0, 0,
+            True, 0, 0,
             "PANORAMA", 0.6, 0.1, -1, False, "GAIN_BLOCKS",
             True, False, -1,
             "Homography", "Multi-Band", True, 5000, 0.5, 5.0, 0.5, 10000, 10000, 15, 4,
@@ -2822,7 +2893,7 @@ with gr.Blocks() as demo:
         ],
         [
             ["examples/cat/cat_left.jpg", "examples/cat/cat_right.jpg"],
-            0, 0,
+            True, 0, 0,
             "SCANS", 0.6, 0.1, -1, False, "GAIN_BLOCKS",
             True, False, -1,
             "Affine_Partial", "Linear", True, 5000, 0.5, 5.0, 0.5, 10000, 10000, 15, 4,
@@ -2830,7 +2901,7 @@ with gr.Blocks() as demo:
         ],
         [
             ["examples/ギルドの受付嬢ですが/Girumasu_1.jpg", "examples/ギルドの受付嬢ですが/Girumasu_2.jpg", "examples/ギルドの受付嬢ですが/Girumasu_3.jpg"],
-            0, 0,
+            True, 0, 0,
             "PANORAMA", 0.6, 0.1, -1, False, "GAIN_BLOCKS",
             True, False, -1,
             "Affine_Partial", "Linear", True, 5000, 0.65, 5.0, 0.5, 10000, 10000, 15, 4,
@@ -2838,7 +2909,7 @@ with gr.Blocks() as demo:
         ],
         [
             ["examples/photographs1/img1.jpg", "examples/photographs1/img2.jpg", "examples/photographs1/img3.jpg", "examples/photographs1/img4.jpg"],
-            0, 0,
+            True, 0, 0,
             "PANORAMA", 0.6, 0.1, -1, True, "GAIN_BLOCKS",
             True, False, -1,
             "Homography", "Linear", True, 5000, 0.5, 5.0, 0.5, 10000, 10000, 15, 4,

webui.bat

@@ -1,21 +1,37 @@
 @echo off
 
-:: The source of the webui.bat file is stable-diffusion-webui
-:: set COMMANDLINE_ARGS=--whisper_implementation faster-whisper --input_audio_max_duration -1 --default_model_name large-v2 --auto_parallel True --output_dir output --vad_max_merge_size 90 --save_downloaded_files --autolaunch
+:: The original source of the webui.bat file is stable-diffusion-webui
+:: Modified and enhanced by Gemini with features for venv management and requirements handling.
 
+:: --------- Configuration ---------
+set COMMANDLINE_ARGS=
+:: Define the name of the Launch application
+set APPLICATION_NAME=app.py
+:: Define the name of the virtual environment directory
+set VENV_NAME=venv
+:: Set to 1 to always attempt to update packages from requirements.txt on every launch
+set ALWAYS_UPDATE_REQS=0
+:: ---------------------------------
+
+
+:: Set PYTHON executable if not already defined
 if not defined PYTHON (set PYTHON=python)
-if not defined VENV_DIR (set "VENV_DIR=%~dp0%venv")
+:: Set VENV_DIR using VENV_NAME if not already defined
+if not defined VENV_DIR (set "VENV_DIR=%~dp0%VENV_NAME%")
 
 mkdir tmp 2>NUL
 
+:: Check if Python is callable
 %PYTHON% -c "" >tmp/stdout.txt 2>tmp/stderr.txt
 if %ERRORLEVEL% == 0 goto :check_pip
 echo Couldn't launch python
 goto :show_stdout_stderr
 
 :check_pip
+:: Check if pip is available
 %PYTHON% -mpip --help >tmp/stdout.txt 2>tmp/stderr.txt
 if %ERRORLEVEL% == 0 goto :start_venv
+:: If pip is not available and PIP_INSTALLER_LOCATION is set, try to install pip
 if "%PIP_INSTALLER_LOCATION%" == "" goto :show_stdout_stderr
 %PYTHON% "%PIP_INSTALLER_LOCATION%" >tmp/stdout.txt 2>tmp/stderr.txt
 if %ERRORLEVEL% == 0 goto :start_venv
@@ -23,33 +39,106 @@ echo Couldn't install pip
 goto :show_stdout_stderr
 
 :start_venv
-if ["%VENV_DIR%"] == ["-"] goto :skip_venv
-if ["%SKIP_VENV%"] == ["1"] goto :skip_venv
+:: Skip venv creation/activation if VENV_DIR is explicitly set to "-"
+if ["%VENV_DIR%"] == ["-"] goto :skip_venv_entirely
+:: Skip venv creation/activation if SKIP_VENV is set to "1"
+if ["%SKIP_VENV%"] == ["1"] goto :skip_venv_entirely
 
+:: Check if the venv already exists by looking for Python.exe in its Scripts directory
 dir "%VENV_DIR%\Scripts\Python.exe" >tmp/stdout.txt 2>tmp/stderr.txt
-if %ERRORLEVEL% == 0 goto :activate_venv
+if %ERRORLEVEL% == 0 goto :activate_venv_and_maybe_update
 
+:: Venv does not exist, create it
+echo Virtual environment not found in "%VENV_DIR%". Creating a new one.
 for /f "delims=" %%i in ('CALL %PYTHON% -c "import sys; print(sys.executable)"') do set PYTHON_FULLNAME="%%i"
 echo Creating venv in directory %VENV_DIR% using python %PYTHON_FULLNAME%
 %PYTHON_FULLNAME% -m venv "%VENV_DIR%" >tmp/stdout.txt 2>tmp/stderr.txt
-if %ERRORLEVEL% == 0 goto :activate_venv
-echo Unable to create venv in directory "%VENV_DIR%"
-goto :show_stdout_stderr
-
-:activate_venv
+if %ERRORLEVEL% NEQ 0 (
+    echo Unable to create venv in directory "%VENV_DIR%"
+    goto :show_stdout_stderr
+)
+echo Venv created.
+
+:: Install requirements for the first time if venv was just created
+:: This section handles the initial installation of packages from requirements.txt
+:: immediately after a new virtual environment is created.
+echo Checking for requirements.txt for initial setup in %~dp0
+if exist "%~dp0requirements.txt" (
+    echo Found requirements.txt, attempting to install for initial setup...
+    call "%VENV_DIR%\Scripts\activate.bat"
+    echo Installing packages from requirements.txt ^(initial setup^)...
+    "%VENV_DIR%\Scripts\python.exe" -m pip install -r "%~dp0requirements.txt"
+    if %ERRORLEVEL% NEQ 0 (
+        echo Failed to install requirements during initial setup. Please check the output above.
+        pause
+        goto :show_stdout_stderr_custom_pip_initial 
+    )
+    echo Initial requirements installed successfully.
+    call "%VENV_DIR%\Scripts\deactivate.bat"
+) else (
+    echo No requirements.txt found for initial setup, skipping package installation.
+)
+goto :activate_venv_and_maybe_update
+
+
+:activate_venv_and_maybe_update
+:: This label is reached if the venv exists or was just created.
+:: Set PYTHON to point to the venv's Python interpreter.
 set PYTHON="%VENV_DIR%\Scripts\Python.exe"
-echo venv %PYTHON%
+echo Activating venv: %PYTHON%
+
+:: Always update requirements if ALWAYS_UPDATE_REQS is 1
+:: This section allows for updating packages from requirements.txt on every launch
+:: if the ALWAYS_UPDATE_REQS variable is set to 1.
+if defined ALWAYS_UPDATE_REQS (
+    if "%ALWAYS_UPDATE_REQS%"=="1" (
+        echo ALWAYS_UPDATE_REQS is enabled.
+        if exist "%~dp0requirements.txt" (
+            echo Attempting to update packages from requirements.txt...
+            REM No need to call activate.bat here again, PYTHON is already set to the venv's python
+            %PYTHON% -m pip install -r "%~dp0requirements.txt"
+            if %ERRORLEVEL% NEQ 0 (
+                echo Failed to update requirements. Please check the output above.
+                pause
+                goto :endofscript 
+            )
+            echo Requirements updated successfully.
+        ) else (
+            echo ALWAYS_UPDATE_REQS is enabled, but no requirements.txt found. Skipping update.
+        )
+    ) else (
+        echo ALWAYS_UPDATE_REQS is not enabled or not set to 1. Skipping routine update.
+    )
+)
 
-:skip_venv
+goto :launch
+
+:skip_venv_entirely
+:: This label is reached if venv usage is explicitly skipped.
+echo Skipping venv.
 goto :launch
 
 :launch
-%PYTHON% app.py %COMMANDLINE_ARGS% %*
+:: Launch the main application
+echo Launching Web UI with arguments: %COMMANDLINE_ARGS% %*
+%PYTHON% %APPLICATION_NAME% %COMMANDLINE_ARGS% %*
+echo Launch finished.
 pause
 exit /b
 
-:show_stdout_stderr
+:show_stdout_stderr_custom_pip_initial
+:: Custom error handler for failures during the initial pip install process.
+echo.
+echo exit code ^(pip initial install^): %errorlevel%
+echo Errors during initial pip install. See output above.
+echo.
+echo Launch unsuccessful. Exiting.
+pause
+exit /b
 
+
+:show_stdout_stderr
+:: General error handler: displays stdout and stderr from the tmp directory.
 echo.
 echo exit code: %errorlevel%
 
@@ -61,13 +150,13 @@ type tmp\stdout.txt
 
 :show_stderr
 for /f %%i in ("tmp\stderr.txt") do set size=%%~zi
-if %size% equ 0 goto :show_stderr
+if %size% equ 0 goto :endofscript
 echo.
 echo stderr:
 type tmp\stderr.txt
 
 :endofscript
-
 echo.
 echo Launch unsuccessful. Exiting.
 pause
+exit /b