still initial commit

app.py

@@ -3,23 +3,38 @@ import cv2
 import numpy as np
 import gradio as gr
 import modal
+from datetime import datetime
+
+# ── Logging Setup ───────────────────────────────────────────────────────────
+init_logs = []
+
+def log_system_event(message: str):
+    """Formats logs with a timestamp and syncs to stdout and UI."""
+    timestamp = datetime.now().strftime("%H:%M:%S")
+    formatted_log = f"[{timestamp}] {message}"
+    print(formatted_log)
+    init_logs.append(formatted_log)
+
+# ── Modal Backend Connection ────────────────────────────────────────────────
+log_system_event("Initializing connection to Modal remote infrastructure...")
 
-# ── Modal Backend ───────────────────────────────────────────────────────────
 try:
     VoxelModelCls = modal.Cls.from_name("flux-klein-voxel-backend", "VoxelModel")
     voxel_backend = VoxelModelCls().process_frame
-    print("✅ Modal Cls connected.")
+    log_system_event("✅ Success: Bound directly to Modal Class deployment ('VoxelModel').")
 except Exception as e:
+    log_system_event(f"⚠️ Modal Class lookup failed ({e}). Attempting fallback function router...")
     try:
         voxel_backend = modal.Function.from_name("flux-klein-voxel-backend", "demo_stream_frame")
-        print("✅ Modal Function connected.")
+        log_system_event("✅ Success: Hooked into fallback standalone Modal Function.")
     except Exception as ex:
-        print(f"❌ Modal backend offline: {ex}")
+        log_system_event(f"❌ Critical: All remote Modal endpoints are unreachable. Error: {ex}")
         voxel_backend = None
 
 status_color = "🟢" if voxel_backend is not None else "🔴"
 status_text  = "Connected" if voxel_backend is not None else "Offline"
 
+
 # ── Helpers ─────────────────────────────────────────────────────────────────
 def _offline_frame(frame: np.ndarray, message: str) -> np.ndarray:
     """Generates a styled placeholder frame when backend is offline."""
@@ -29,6 +44,7 @@ def _offline_frame(frame: np.ndarray, message: str) -> np.ndarray:
                 cv2.FONT_HERSHEY_DUPLEX, 0.8, (0, 0, 220), 2)
     return out
 
+
 def _run_voxel_backend(frame: np.ndarray) -> np.ndarray:
     """Encodes and ships raw image bytes to the Modal worker."""
     success, encoded = cv2.imencode(".jpg", frame, [int(cv2.IMWRITE_JPEG_QUALITY), 85])
@@ -44,20 +60,33 @@ def _run_voxel_backend(frame: np.ndarray) -> np.ndarray:
                     cv2.FONT_HERSHEY_SIMPLEX, 0.55, (0, 0, 255), 1)
         return out
 
+
 # ── Core Stream Handler ─────────────────────────────────────────────────────
-def process_video_stream(frame: np.ndarray, mode: str) -> np.ndarray:
+frame_counter = 0
+
+def process_video_stream(frame: np.ndarray, mode: str, is_running: bool) -> np.ndarray:
     """
-    Accepts incoming frame from the webcam and the mode dropdown selection.
+    Accepts incoming frame from the webcam, pipeline settings, and execution state flag.
     """
+    global frame_counter
     if frame is None:
         return None
 
+    # If user hasn't toggled "Start Processing", safely pass raw video back as preview
+    if not is_running:
+        return frame
+
     if voxel_backend is None:
         err_frame = _offline_frame(frame, "Modal Backend Offline")
         if mode == "Streaming Demo":
             return np.hstack([frame, err_frame])
         return err_frame
 
+    # Runtime console indicator: logs transmission health to terminal every 15 frames
+    frame_counter += 1
+    if frame_counter % 15 == 0:
+        print(f"🚀 [LIVE PIPELINE] Actively transmitting frames. Dispatched {frame_counter} payloads to Modal worker.")
+
     # Process via the lightweight single-image pipeline
     processed = _run_voxel_backend(frame)
 
@@ -77,17 +106,29 @@ def process_video_stream(frame: np.ndarray, mode: str) -> np.ndarray:
 
     return processed
 
+
 # ── Custom Gradio Interface Layout ──────────────────────────────────────────
 with gr.Blocks(title="⛏️ Minecraft Spatial Voxel Filter") as demo:
+    # State tracking engine variable
+    is_running = gr.State(value=False)
+    
     gr.Markdown("# ⛏️ Minecraft Spatial Voxel Filter")
     
     with gr.Row():
-        # Configuration Settings & Status (Left Side Box)
+        # Configuration Settings & Log Panel (Left Column)
         with gr.Column(scale=1):
             gr.Markdown(
                 f"### ⚡ Backend Connection Status\n"
-                f"Status: {status_color} **{status_text}**\n\n"
-                f"Switching between pipeline modes instantly updates your active viewport feed."
+                f"Status: {status_color} **{status_text}**"
+            )
+            
+            # Live Diagnostic Log Display View
+            ui_logs = gr.Textbox(
+                value="\n".join(init_logs),
+                label="💻 System Initialization Logs",
+                lines=6,
+                max_lines=10,
+                interactive=False,
             )
             
             mode_dropdown = gr.Dropdown(
@@ -97,15 +138,23 @@ with gr.Blocks(title="⛏️ Minecraft Spatial Voxel Filter") as demo:
                 interactive=True,
             )
             
-        # Standard Gradio Streaming Setup (Right Side Box)
+            with gr.Row():
+                start_btn = gr.Button("🚀 Start Processing", variant="primary")
+                stop_btn = gr.Button("🛑 Stop", variant="secondary")
+            
+        # Video Capture Viewports (Right Column)
         with gr.Column(scale=2):
             input_stream = gr.Image(sources=["webcam"], streaming=True, label="Live Webcam Input")
             output_stream = gr.Image(interactive=False, label="Voxel Output Viewport")
 
-    # Native Gradio stream event triggers whenever a new frame comes from the webcam
+    # Wire up button interface trigger mappings to flip our State flag
+    start_btn.click(fn=lambda: True, inputs=None, outputs=is_running)
+    stop_btn.click(fn=lambda: False, inputs=None, outputs=is_running)
+
+    # Core engine transmission loop
     input_stream.stream(
         fn=process_video_stream,
-        inputs=[input_stream, mode_dropdown],
+        inputs=[input_stream, mode_dropdown, is_running],
         outputs=[output_stream]
     )