Update app.py

app.py

@@ -1,79 +1 @@
-# app.py
-import cv2
-import gradio as gr
-from ultralytics import YOLO
-
-# ── Config ─────────────────────────────────────────────
-MODEL_PATH = "yolov8n.pt"     # modelo pre-entrenado (COCO, clase “person”)
-CONF_THRES = 0.3              # confianza mínima
-LINE_RATIO = 0.5              # línea virtual en mitad de la altura
-# ───────────────────────────────────────────────────────
-
-model = YOLO(MODEL_PATH)
-
-# Estado global para entradas/salidas
-memory = {}      # {track_id: previous_cy}
-in_count = 0
-out_count = 0
-
-def count_people(frame):
-    global memory, in_count, out_count
-
-    h, w = frame.shape[:2]
-    line_y = int(h * LINE_RATIO)
-
-    # detección + tracking interno (ByteTrack)
-    results = model.track(
-        frame,
-        classes=[0],        # solo “person”
-        conf=CONF_THRES,
-        persist=True,
-        verbose=False
-    )
-
-    annotated = frame.copy()
-    cv2.line(annotated, (0, line_y), (w, line_y), (0, 255, 255), 2)
-
-    if results:
-        for box in results[0].boxes:
-            x1, y1, x2, y2 = map(int, box.xyxy[0])
-            cx, cy = int((x1 + x2) / 2), int((y1 + y2) / 2)
-            tid = int(box.id[0]) if box.id is not None else -1
-
-            # lógica de cruce
-            prev_cy = memory.get(tid, cy)
-            if prev_cy < line_y <= cy:        # entra
-                in_count += 1
-            elif prev_cy > line_y >= cy:      # sale
-                out_count += 1
-            memory[tid] = cy
-
-            # dibujo
-            cv2.rectangle(annotated, (x1, y1), (x2, y2), (0, 255, 0), 1)
-            cv2.circle(annotated, (cx, cy), 3, (0, 0, 255), -1)
-            cv2.putText(annotated, str(tid), (x1, y1 - 5),
-                        cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 0, 0), 1)
-
-    total = in_count - out_count
-    cv2.putText(
-        annotated,
-        f"In: {in_count}  Out: {out_count}  Ocupación: {total}",
-        (10, 30),
-        cv2.FONT_HERSHEY_SIMPLEX,
-        1,
-        (255, 255, 255),
-        2
-    )
-
-    return annotated, f"In: {in_count} | Out: {out_count} | Ocupación: {total}"
-
-demo = gr.Interface(
-    fn=count_people,
-    inputs=gr.Image(sources=["webcam"], streaming=True),  # 👈 parámetro correcto
-    outputs=[gr.Image(label="Video"), gr.Text(label="Contador")],
-    live=True,
-    title="Contador de personas (entrada única)"
-)
-
-if __name__ == "__main__":
-    demo.launch()
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b22e8eb38ed4c779d540fc/rkXD8FcVjo6w33hleoJvs.png)