Porting All features from RKNN to Jetson

API.md

@@ -0,0 +1,220 @@
+# counter_dashboard.py — API Documentation
+
+## Page
+
+### `GET /`
+Renders the main dashboard HTML page (`dashboard.html`).
+
+---
+
+## API Endpoints
+
+### `GET /api/live-video`
+MJPEG streaming endpoint. Serves live frames from the path configured in `LIVE_STREAM_FRAME_PATH` (default `/dev/shm/jetson-counter/live_frame.jpg`) as `multipart/x-mixed-replace`.
+
+**Response:** JPEG stream with `--frame` boundary delimiters.
+
+---
+
+### `GET /api/current-batch`
+Returns the currently active batch's data read from `current_batch.json`.
+
+**Success response:**
+```json
+{
+  "success": true,
+  "counting_date": "2024-01-01",
+  "batch_number": 12,
+  "count": 342,
+  "start_time": "2024-01-01T14:30:00",
+  "last_detection_time": "2024-01-01T14:35:00"
+}
+```
+
+**Error response (no active batch, 200):**
+```json
+{
+  "success": false,
+  "error": "No active batch",
+  "count": 0,
+  "batch_number": null,
+  "counting_date": null
+}
+```
+
+---
+
+### `GET /api/previous-batch`
+Returns the most recently completed batch from the `batches` database table, with computed `duration_minutes`.
+
+**Success response:**
+```json
+{
+  "success": true,
+  "date": "2024-01-01",
+  "batch_number": 11,
+  "count": 287,
+  "start_time": "2024-01-01T14:00:00",
+  "end_time": "2024-01-01T14:27:00",
+  "duration_minutes": 27.0
+}
+```
+
+---
+
+### `GET /api/summary`
+Returns today, yesterday, and all-time aggregate statistics plus average per day and best day.
+
+**Success response:**
+```json
+{
+  "today": {
+    "date": "2024-01-01",
+    "total_count": 1500,
+    "total_batches": 8
+  },
+  "yesterday": {
+    "date": "2023-12-31",
+    "total_count": 1342,
+    "total_batches": 7
+  },
+  "all_time": {
+    "grand_total": 50000,
+    "grand_batches": 260,
+    "total_days": 45
+  },
+  "average_per_day": 1111.1,
+  "best_day": {
+    "date": "2023-12-15",
+    "count": 2100
+  }
+}
+```
+
+---
+
+### `GET /api/daily-data`
+Returns daily summary rows for charting.
+
+**Query params:**
+| Param  | Type | Default | Description                     |
+|--------|------|---------|---------------------------------|
+| `days` | int  | 30      | Number of days to look back     |
+
+**Response:**
+```json
+[
+  {
+    "date": "2024-01-01",
+    "total_count": 1500,
+    "total_batches": 8,
+    "avg_per_batch": 187.5
+  }
+]
+```
+
+---
+
+### `GET /api/day-detail/<date>`
+Returns all batch records for a specific `counting_date` along with summary totals.
+
+**Path params:**
+| Param  | Type   | Description            |
+|--------|--------|------------------------|
+| `date` | string | Date in `YYYY-MM-DD`   |
+
+**Success response:**
+```json
+{
+  "date": "2024-01-01",
+  "total_count": 1500,
+  "total_batches": 8,
+  "total_duration_minutes": 216.0,
+  "avg_duration_minutes": 27.0,
+  "batches": [
+    {
+      "batch_number": 1,
+      "count": 187,
+      "start_time": "2024-01-01T08:00:00",
+      "end_time": "2024-01-01T08:27:00",
+      "duration_minutes": 27.0
+    }
+  ]
+}
+```
+
+---
+
+### `GET /api/recent-batches`
+Returns the most recent batches with computed durations.
+
+**Query params:**
+| Param   | Type | Default | Description                     |
+|---------|------|---------|---------------------------------|
+| `limit` | int  | 10      | Max number of batches to return |
+
+**Response:**
+```json
+[
+  {
+    "date": "2024-01-01",
+    "batch_number": 8,
+    "count": 213,
+    "start_time": "2024-01-01T16:30:00",
+    "end_time": "2024-01-01T16:58:00",
+    "duration_minutes": 28.0
+  }
+]
+```
+
+---
+
+### `GET /api/available-dates`
+Returns all dates with data from the `daily_summaries` table, ordered by date descending.
+
+**Response:**
+```json
+[
+  {
+    "date": "2024-01-01",
+    "total_count": 1500,
+    "total_batches": 8
+  }
+]
+```
+
+---
+
+## Export Endpoints (XLSX)
+
+### `GET /api/export-daily-csv`
+Exports batch detail records for the last N days as an `.xlsx` file.
+
+**Query params:**
+| Param  | Type | Default | Description                 |
+|--------|------|---------|-----------------------------|
+| `days` | int  | 30      | Number of days to look back |
+
+**Response:** XLSX file download with columns: Date, Batch #, Count, Start Time, End Time, Duration (min).
+
+Filename format: `{SITE_NAME}_daily_records_{timestamp}.xlsx`
+
+---
+
+### `GET /api/export-day-csv/<date>`
+Exports all batch records for a single date as an `.xlsx` file.
+
+**Path params:**
+| Param  | Type   | Description          |
+|--------|--------|----------------------|
+| `date` | string | Date in `YYYY-MM-DD` |
+
+**Response:** XLSX file download with columns: Batch Number, Count, Start Time, End Time, Duration (min).
+
+Filename format: `{SITE_NAME}_day_detail_{date}.xlsx`
+
+---
+
+## Error Handling
+
+All endpoints return `{"success": false, "error": "<message>"}` with HTTP 500 on unexpected errors. Database-unavailable errors (`sqlite3.OperationalError`) return HTTP 200 with an empty/default data structure. The `/api/live-video` endpoint returns HTTP 503 if the frame file is not found.

counter_live_jetson.py

@@ -9,6 +9,7 @@ import numpy as np
 import os
 import signal
 import time
+from collections import deque
 from datetime import datetime
 from pathlib import Path
 
@@ -68,6 +69,11 @@ RTSP_FFMPEG_OPTIONS = os.getenv(
 
 IS_LIVE = SOURCE.lower().startswith(('rtsp://', 'http://'))
 
+MOTION_DETECTION_ENABLED = os.getenv('MOTION_DETECTION_ENABLED', 'false').lower() == 'true'
+MOTION_THRESHOLD = float(os.getenv('MOTION_THRESHOLD', '5.0'))
+
+RATE_WINDOW_SEC = int(os.getenv('RATE_WINDOW_SEC', '60'))
+
 CROSS_FLASH_FRAMES = 12
 POPUP_LIFETIME = 20
 LINE_PULSE_FRAMES = 12
@@ -251,12 +257,12 @@ def draw_hero_count(img, line_x, h, count, pulse_remaining=0):
     text = str(count)
     font = cv2.FONT_HERSHEY_SIMPLEX
     boost = 0.35 * (pulse_remaining / max(COUNT_PULSE_FRAMES, 1))
-    font_scale, thickness = 1.6 + boost, 3
+    font_scale, thickness = 1.4 + boost, 3
     (tw, th), _ = cv2.getTextSize(text, font, font_scale, thickness)
     pad = 14
-    tx, ty = line_x - tw // 2, h // 2 + th // 2
+    tx, ty = line_x - tw // 2, h // 3 + th // 2
-    overlay_rect(img, tx - pad, ty - th - pad, tx + tw + pad, ty + pad // 2, C_PANEL, alpha=0.78)
+    overlay_rect(img, tx - pad, ty - th - pad, tx + tw + pad, ty + pad, C_PANEL, alpha=0.78)
-    cv2.rectangle(img, (tx - pad, ty - th - pad), (tx + tw + pad, ty + pad // 2), C_LINE_CORE, 2)
+    cv2.rectangle(img, (tx - pad, ty - th - pad), (tx + tw + pad, ty + pad), C_LINE_CORE, 2)
     cv2.putText(img, text, (tx, ty), font, font_scale, C_GREEN, thickness, cv2.LINE_AA)
 
 
@@ -279,10 +285,10 @@ def draw_hud(img, w, batch_num, batch_count, total_ayam, elapsed_sec, rate, came
     cv2.putText(img, f'CAM {camera_id}', (w - 180, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA)
 
 
-def draw_footer(img, w, h, frame_idx, live_tag):
+def draw_footer(img, w, h, frame_idx, live_tag, inf_ms=0.0, model_name=''):
     bar_h = 28
     overlay_rect(img, 0, h - bar_h, w, h, C_PANEL, alpha=0.55)
-    cv2.putText(img, f'{live_tag} | Frame {frame_idx}', (12, h - 9), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA)
+    cv2.putText(img, f'{live_tag} | {model_name} | Frame {frame_idx} | Inf {inf_ms:.1f}ms', (12, h - 9), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA)
 
 
 def draw_skeleton_bold(img, kpts):
@@ -384,7 +390,10 @@ def run():
 
     session_start = time.time()
     frame_idx = 0
+    inf_ms = 0.0
     video_writer = None
+    crossing_times = deque()
+    prev_gray = None
 
     cap, w, h, fps = connect_stream(SOURCE)
     if cap is None:
@@ -422,19 +431,34 @@ def run():
         mono = time.monotonic()
         ayam_crossed_frame = batch_closed_frame = batch_started_frame = False
 
-        results = model.track(
+        skip_inference = False
-            frame,
+        if MOTION_DETECTION_ENABLED:
-            device=DEVICE,
+            gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
-            persist=True,
+            if prev_gray is not None:
-            conf=CONF,
+                diff = cv2.absdiff(gray, prev_gray)
-            imgsz=IMGSZ,
+                mean_diff = cv2.mean(diff)[0]
-            half=HALF,
+                skip_inference = mean_diff < MOTION_THRESHOLD
-            tracker=TRACKER,
+            prev_gray = gray
-            verbose=False,
+
-        )
+        if not skip_inference:
+            inf_start = time.time()
+            results = model.track(
+                frame,
+                device=DEVICE,
+                persist=True,
+                conf=CONF,
+                imgsz=IMGSZ,
+                half=HALF,
+                tracker=TRACKER,
+                verbose=False,
+            )
+            inf_ms = inf_ms * 0.9 + (time.time() - inf_start) * 1000 * 0.1
+        else:
+            results = [None]
+
         r = results[0]
 
-        if r.boxes.id is not None:
+        if r is not None and r.boxes.id is not None:
             ids = r.boxes.id.int().tolist()
             boxes = r.boxes.xyxy.tolist()
             clss = r.boxes.cls.int().tolist()
@@ -474,12 +498,29 @@ def run():
                                 datetime.now().isoformat(), track_id,
                             ])
                         ayam_crossed_frame = True
+                        crossing_times.append(mono)
                         if started_new:
                             batch_started_frame = True
                         ayam_cross_flash[track_id] = CROSS_FLASH_FRAMES
                         popups.append({'x': cx - 12, 'y': (y1 + y2) // 2, 'born': frame_idx, 'text': '+1'})
                 ayam_tracked[track_id] = (cx, mono)
 
+            if os.getenv('DEBUG_TRACKING', '').lower() == 'true':
+                ayam_tracks_str = f'  ayam_tracked: {sorted(ayam_tracked.keys())}' if ayam_tracked else ''
+                talenan_tracks_str = f'  talenan_tracked: {sorted(talenan_tracked.keys())}' if talenan_tracked else ''
+                cx_sample = ''
+                if ayam_items:
+                    track_id, cx, _, _, _, _, _ = ayam_items[0]
+                    prev = ayam_tracked.get(track_id, (None,))[0] if ayam_tracked.get(track_id) else None
+                    cx_sample = f'  sample tid={track_id} prev_cx={prev} cx={cx}'
+                print(
+                    f'[DEBUG F{frame_idx}] ayam_dets={len(ayam_items)} '
+                    f'talenan_dets={len(talenan_items)} '
+                    f'line_x={line_x}{talenan_tracks_str}{ayam_tracks_str}'
+                    f'  crossed: a={sorted(ayam_line_crossed)} t={sorted(talenan_line_crossed)}'
+                    f'{cx_sample}'
+                )
+
             for track_id, cx, x1, y1, x2, y2, _ in talenan_items:
                 flash = talenan_cross_flash.get(track_id, 0)
                 color = C_GREEN if flash > 0 else C_TALENAN_BOX
@@ -505,13 +546,15 @@ def run():
         batch_num = store.current_batch_number or 0
         batch_count = store.current_batch_count
         display_total = store.display_total()
-        rate = (display_total / elapsed * 60) if elapsed > 0 else 0.0
+        while crossing_times and mono - crossing_times[0] > RATE_WINDOW_SEC:
+            crossing_times.popleft()
+        rate = (len(crossing_times) / RATE_WINDOW_SEC * 60) if crossing_times else 0.0
 
         draw_elegant_counting_line(frame, line_x, h, line_pulse)
         draw_hero_count(frame, line_x, h, batch_count, count_pulse)
         draw_hud(frame, w, batch_num, batch_count, display_total, elapsed, rate, CAMERA_NAME, now_str())
         draw_batch_banner(frame, w, batch_num, batch_pulse)
-        draw_footer(frame, w, h, frame_idx, 'LIVE' if IS_LIVE else 'FILE')
+        draw_footer(frame, w, h, frame_idx, 'LIVE' if IS_LIVE else 'FILE', inf_ms, Path(MODEL_PATH).name)
         popups = draw_popups(frame, popups, frame_idx)
 
         for flash_store in (ayam_cross_flash, talenan_cross_flash):