Create app.py

app.py

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+"""
+Videodagi odamlar sonini hisoblash — People Counter
+YOLOv8 + ByteTrack/SORT tracker yordamida
+"""
+
+import gradio as gr
+import cv2
+import numpy as np
+import tempfile
+import os
+from collections import defaultdict
+from ultralytics import YOLO
+
+# ── Model yuklash ──────────────────────────────────────────────
+model = YOLO("yolov8n.pt")   # nano — tez, yengil, yetarli aniqlik
+PERSON_CLASS = 0             # COCO dataset: 0 = person
+
+# ── Tracker state (har bir video uchun yangilanadi) ────────────
+class SimpleTracker:
+    """
+    IoU-asosidagi sodda tracker.
+    Har bir frame'dagi detection'larni oldingi track'lar bilan solishtiradi.
+    Yangi track_id berib, unique odamlar sonini hisoblaydi.
+    """
+    def __init__(self, iou_threshold=0.3, max_lost=30):
+        self.tracks       = {}          # track_id -> {'bbox': ..., 'lost': 0}
+        self.next_id      = 1
+        self.unique_ids   = set()
+        self.iou_thr      = iou_threshold
+        self.max_lost     = max_lost
+
+    def _iou(self, a, b):
+        ax1, ay1, ax2, ay2 = a
+        bx1, by1, bx2, by2 = b
+        ix1, iy1 = max(ax1, bx1), max(ay1, by1)
+        ix2, iy2 = min(ax2, bx2), min(ay2, by2)
+        inter = max(0, ix2 - ix1) * max(0, iy2 - iy1)
+        if inter == 0:
+            return 0.0
+        ua = (ax2-ax1)*(ay2-ay1) + (bx2-bx1)*(by2-by1) - inter
+        return inter / ua if ua > 0 else 0.0
+
+    def update(self, detections):
+        """detections: list of [x1,y1,x2,y2]"""
+        # ── 1. Mavjud track'larni detectionlar bilan moslashtir
+        matched_track_ids = set()
+        matched_det_idxs  = set()
+
+        track_ids = list(self.tracks.keys())
+        for det_idx, det_bbox in enumerate(detections):
+            best_iou, best_tid = 0, None
+            for tid in track_ids:
+                if tid in matched_track_ids:
+                    continue
+                iou = self._iou(det_bbox, self.tracks[tid]['bbox'])
+                if iou > best_iou:
+                    best_iou, best_tid = iou, tid
+            if best_iou >= self.iou_thr and best_tid is not None:
+                self.tracks[best_tid]['bbox'] = det_bbox
+                self.tracks[best_tid]['lost'] = 0
+                matched_track_ids.add(best_tid)
+                matched_det_idxs.add(det_idx)
+
+        # ── 2. Mos kelmagan detectionlar → yangi track
+        for det_idx, det_bbox in enumerate(detections):
+            if det_idx not in matched_det_idxs:
+                tid = self.next_id
+                self.next_id += 1
+                self.tracks[tid] = {'bbox': det_bbox, 'lost': 0}
+                self.unique_ids.add(tid)
+
+        # ── 3. Mos kelmagan track'lar → lost++
+        for tid in track_ids:
+            if tid not in matched_track_ids:
+                self.tracks[tid]['lost'] += 1
+
+        # ── 4. Ko'p yo'qolgan track'larni o'chir
+        self.tracks = {
+            tid: v for tid, v in self.tracks.items()
+            if v['lost'] < self.max_lost
+        }
+
+        return {
+            tid: v['bbox']
+            for tid, v in self.tracks.items()
+            if v['lost'] == 0
+        }
+
+
+# ── Asosiy hisoblash funksiyasi ────────────────────────────────
+def count_people(video_path, conf_threshold=0.4, progress=gr.Progress()):
+    if video_path is None:
+        return None, "❌ Video yuklanmadi."
+
+    cap = cv2.VideoCapture(video_path)
+    if not cap.isOpened():
+        return None, "❌ Video ochilmadi."
+
+    # Video parametrlari
+    total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
+    fps          = cap.get(cv2.CAP_PROP_FPS) or 25
+    width        = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
+    height       = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
+
+    # Output video (annotated)
+    out_path = tempfile.mktemp(suffix="_result.mp4")
+    fourcc   = cv2.VideoWriter_fourcc(*"mp4v")
+    writer   = cv2.VideoWriter(out_path, fourcc, fps, (width, height))
+
+    tracker   = SimpleTracker(iou_threshold=0.3, max_lost=int(fps * 1.5))
+    frame_idx = 0
+
+    # Rang palitasi
+    COLORS = [
+        (255, 80,  80),  (80, 200, 120), (80, 160, 255),
+        (255, 200,  50), (200,  80, 255),(50, 220, 220),
+    ]
+
+    while True:
+        ret, frame = cap.read()
+        if not ret:
+            break
+
+        # ── YOLO detection
+        results = model(frame, classes=[PERSON_CLASS],
+                        conf=conf_threshold, verbose=False)[0]
+
+        detections = []
+        for box in results.boxes:
+            x1, y1, x2, y2 = map(int, box.xyxy[0])
+            detections.append([x1, y1, x2, y2])
+
+        # ── Tracking
+        active_tracks = tracker.update(detections)
+
+        # ── Annotate frame
+        for tid, (x1, y1, x2, y2) in active_tracks.items():
+            color = COLORS[tid % len(COLORS)]
+            cv2.rectangle(frame, (x1, y1), (x2, y2), color, 2)
+            label = f"#{tid}"
+            (tw, th), _ = cv2.getTextSize(label, cv2.FONT_HERSHEY_SIMPLEX, 0.6, 2)
+            cv2.rectangle(frame, (x1, y1 - th - 8), (x1 + tw + 6, y1), color, -1)
+            cv2.putText(frame, label, (x1 + 3, y1 - 4),
+                        cv2.FONT_HERSHEY_SIMPLEX, 0.6, (255, 255, 255), 2)
+
+        # ── Counter overlay
+        total_unique = len(tracker.unique_ids)
+        currently    = len(active_tracks)
+        overlay_text = f"Jami: {total_unique} ta odam"
+        cv2.rectangle(frame, (8, 8), (300, 70), (20, 20, 20), -1)
+        cv2.putText(frame, overlay_text, (14, 36),
+                    cv2.FONT_HERSHEY_SIMPLEX, 0.8, (50, 230, 120), 2)
+        cv2.putText(frame, f"Hozir: {currently} ta", (14, 62),
+                    cv2.FONT_HERSHEY_SIMPLEX, 0.6, (180, 180, 180), 1)
+
+        writer.write(frame)
+        frame_idx += 1
+
+        if total_frames > 0:
+            progress(frame_idx / total_frames, desc=f"Frame {frame_idx}/{total_frames}")
+
+    cap.release()
+    writer.release()
+
+    # ── Natija matni
+    total_unique = len(tracker.unique_ids)
+    if total_unique == 0:
+        result_text = "🚶 Odam yo'q"
+    elif total_unique == 1:
+        result_text = "✅ 1 ta odam"
+    else:
+        result_text = f"✅ {total_unique} ta odam"
+
+    return out_path, result_text
+
+
+# ── Gradio UI ──────────────────────────────────────────────────
+css = """
+body { font-family: 'Segoe UI', sans-serif; }
+#title { text-align: center; }
+#result-box {
+    font-size: 2rem;
+    font-weight: 700;
+    text-align: center;
+    padding: 1.2rem;
+    background: #1a1a2e;
+    color: #50e37c;
+    border-radius: 12px;
+    border: 2px solid #50e37c44;
+    margin-top: 10px;
+}
+.gr-button-primary { background: #50e37c !important; color: #000 !important; }
+"""
+
+with gr.Blocks(css=css, title="People Counter") as demo:
+    gr.Markdown(
+        "# 👁️ Videodagi Odamlar Sonini Hisoblash\n",
+        elem_id="title"
+    )
+
+    with gr.Row():
+        with gr.Column(scale=1):
+            video_input = gr.Video(label="📹 Video yuklang", sources=["upload"])
+            conf_slider = gr.Slider(
+                minimum=0.2, maximum=0.9, value=0.4, step=0.05,
+                label="Ishonchlilik chegarasi (conf threshold)"
+            )
+            run_btn = gr.Button("▶ Hisoblashni boshlash", variant="primary")
+
+        with gr.Column(scale=1):
+            video_output = gr.Video(label="📊 Annotated natija")
+            result_text  = gr.HTML(
+                value="<div id='result-box'>Natija bu yerda ko'rinadi</div>"
+            )
+
+    def run_and_format(video, conf):
+        out_video, text = count_people(video, conf)
+        html = f"<div id='result-box'>{text}</div>"
+        return out_video, html
+
+    run_btn.click(
+        fn=run_and_format,
+        inputs=[video_input, conf_slider],
+        outputs=[video_output, result_text]
+    )
+
+    gr.Markdown("""
+---
+### Qanday ishlaydi?
+1. **YOLOv8n** — har bir frame'da odamlarni bounding box bilan aniqlaydi  
+2. **IoU Tracker** — bir odamni ketma-ket frame'larda bir xil ID bilan kuzatadi  
+3. **Unique ID sanash** — video davomida paydo bo'lgan barcha yangi ID'lar sanaladi  
+4. **Natija** — "odam yo'q" yoki "N ta odam"
+""")
+
+if __name__ == "__main__":
+    demo.launch()