Update app.py

app.py

@@ -3,42 +3,32 @@ import gradio as gr
 from ultralytics import YOLO
 
 # ── Config ─────────────────────────────────────────────
-MODEL_PATH = "yolov8n.pt"     # modelo pre-entrenado (clase “person”)
-CONF_THRES = 0.3              # confianza mínima detección
-LINE_RATIO = 0.5              # posición de la línea virtual (50 % altura)
+MODEL_PATH = "yolov8n.pt"   # peso pre-entrenado (clase “person”)
+CONF_THRES = 0.3
+LINE_RATIO = 0.5            # línea virtual al 50 % de la altura
 # ───────────────────────────────────────────────────────
 
+# carga una sola vez
 model = YOLO(MODEL_PATH)
 
 # estado global
-memory = {}      # {track_id: previous_cy}
-in_count = 0
-out_count = 0
+memory, in_count, out_count = {}, 0, 0
 
 
-def count_people(frame):
-    """
-    Recibe un frame RGB (numpy) -> procesa -> devuelve frame RGB anotado y string.
-    Se llama de forma continua porque el input tiene `streaming=True`.
-    """
+def count_people(frame_rgb):
+    """Procesa un frame RGB -> devuelve frame RGB anotado + texto contador."""
     global memory, in_count, out_count
 
-    if frame is None:
+    if frame_rgb is None:
         return None, ""
 
-    # ── paso 1: RGB ➜ BGR para OpenCV/YOLO ─────────────
-    frame_bgr = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
+    frame_bgr = cv2.cvtColor(frame_rgb, cv2.COLOR_RGB2BGR)
     h, w = frame_bgr.shape[:2]
     line_y = int(h * LINE_RATIO)
 
-    # ── detección + tracking ───────────────────────────
-    results = model.track(
-        frame_bgr,
-        classes=[0],                 # solo “person”
-        conf=CONF_THRES,
-        persist=True,
-        verbose=False
-    )
+    # detección + tracking
+    results = model.track(frame_bgr, classes=[0], conf=CONF_THRES,
+                          persist=True, verbose=False)
 
     annotated = frame_bgr.copy()
     cv2.line(annotated, (0, line_y), (w, line_y), (0, 255, 255), 2)
@@ -46,18 +36,16 @@ def count_people(frame):
     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)
+            cx, cy = (x1 + x2) // 2, (y1 + y2) // 2
             tid = int(box.id[0]) if box.id is not None else -1
 
-            # cruces entrada / salida
             prev_cy = memory.get(tid, cy)
-            if prev_cy < line_y <= cy:        # cruzó de arriba → abajo (ENTRA)
+            if prev_cy < line_y <= cy:        # entra
                 in_count += 1
-            elif prev_cy > line_y >= cy:      # abajo → arriba (SALE)
+            elif prev_cy > line_y >= cy:      # sale
                 out_count += 1
             memory[tid] = cy
 
-            # dibujitos
             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),
@@ -66,17 +54,13 @@ def count_people(frame):
     total = in_count - out_count
     label = f"In: {in_count} | Out: {out_count} | Ocupación: {total}"
 
-    # ── paso 2: BGR ➜ RGB para mostrar en Gradio ───────
     annotated_rgb = cv2.cvtColor(annotated, cv2.COLOR_BGR2RGB)
     return annotated_rgb, label
 
 
 def reset_counts():
-    """Callback para botón ‘Limpiar’."""
     global memory, in_count, out_count
-    memory = {}
-    in_count = 0
-    out_count = 0
+    memory, in_count, out_count = {}, 0, 0
     return None, ""
 
 
@@ -90,9 +74,9 @@ with gr.Blocks(title="Contador de personas (entrada única)") as demo:
 
     btn_clear = gr.Button("Limpiar")
 
-    # wire-up
-    cam.stream(fn=count_people, outputs=[out_img, out_lbl])
-    btn_clear.click(fn=reset_counts, outputs=[out_img, out_lbl])
+    # 💡 la clave: inputs=[cam]
+    cam.stream(count_people, inputs=[cam], outputs=[out_img, out_lbl])
+    btn_clear.click(reset_counts, outputs=[out_img, out_lbl])
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch(max_threads=2, max_queue=60)  # cola chica para que no se tape