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Update app.py
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app.py
CHANGED
@@ -4,31 +4,38 @@ from ultralytics import YOLO
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# ── Config ─────────────────────────────────────────────
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MODEL_PATH = "yolov8n.pt" # peso pre-entrenado (clase “person”)
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CONF_THRES = 0.
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LINE_RATIO = 0.
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# ───────────────────────────────────────────────────────
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# carga una sola vez
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model = YOLO(MODEL_PATH)
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# estado global
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memory, in_count, out_count = {}, 0, 0
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def count_people(frame_rgb):
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"""
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global memory, in_count, out_count
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if frame_rgb is None:
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return None, ""
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frame_bgr = cv2.cvtColor(frame_rgb, cv2.COLOR_RGB2BGR)
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h, w = frame_bgr.shape[:2]
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line_y = int(h * LINE_RATIO)
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# detección + tracking
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results = model.track(frame_bgr,
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annotated = frame_bgr.copy()
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cv2.line(annotated, (0, line_y), (w, line_y), (0, 255, 255), 2)
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@@ -40,9 +47,9 @@ def count_people(frame_rgb):
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tid = int(box.id[0]) if box.id is not None else -1
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prev_cy = memory.get(tid, cy)
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if prev_cy < line_y <= cy: #
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in_count += 1
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elif prev_cy > line_y >= cy: #
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out_count += 1
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memory[tid] = cy
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@@ -54,16 +61,19 @@ def count_people(frame_rgb):
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total = in_count - out_count
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label = f"In: {in_count} | Out: {out_count} | Ocupación: {total}"
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annotated_rgb = cv2.cvtColor(annotated, cv2.COLOR_BGR2RGB)
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return annotated_rgb, label
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def reset_counts():
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global memory, in_count, out_count
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memory, in_count, out_count = {}, 0, 0
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return None, ""
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with gr.Blocks(title="Contador de personas (entrada única)") as demo:
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gr.Markdown("# Contador de personas (entrada única)")
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@@ -74,9 +84,11 @@ with gr.Blocks(title="Contador de personas (entrada única)") as demo:
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btn_clear = gr.Button("Limpiar")
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#
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cam.stream(count_people, inputs=[cam], outputs=[out_img, out_lbl])
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btn_clear.click(reset_counts, outputs=[out_img, out_lbl])
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if __name__ == "__main__":
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demo.launch(max_threads=2, max_queue=60) # cola chica para que no se tape
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# ── Config ─────────────────────────────────────────────
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MODEL_PATH = "yolov8n.pt" # peso pre-entrenado (clase “person”)
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CONF_THRES = 0.30 # confianza mínima
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LINE_RATIO = 0.50 # posición de la línea virtual (50 % de la altura)
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# ───────────────────────────────────────────────────────
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# modelo — se carga una sola vez
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model = YOLO(MODEL_PATH)
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# estado global del contador
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memory, in_count, out_count = {}, 0, 0
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def count_people(frame_rgb):
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"""
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▸ Recibe un frame RGB (numpy) desde la webcam.
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▸ Devuelve el frame anotado (RGB) y el texto del contador.
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"""
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global memory, in_count, out_count
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if frame_rgb is None:
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return None, ""
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# ── convertir RGB ➜ BGR (OpenCV/YOLO) ──────────────
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frame_bgr = cv2.cvtColor(frame_rgb, cv2.COLOR_RGB2BGR)
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h, w = frame_bgr.shape[:2]
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line_y = int(h * LINE_RATIO)
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# ── detección + tracking (ByteTrack interno) ───────
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results = model.track(frame_bgr,
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classes=[0], # solo “person”
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conf=CONF_THRES,
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persist=True,
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verbose=False)
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annotated = frame_bgr.copy()
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cv2.line(annotated, (0, line_y), (w, line_y), (0, 255, 255), 2)
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tid = int(box.id[0]) if box.id is not None else -1
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prev_cy = memory.get(tid, cy)
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if prev_cy < line_y <= cy: # cruza de arriba → abajo (ENTRA)
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in_count += 1
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elif prev_cy > line_y >= cy: # cruza de abajo → arriba (SALE)
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out_count += 1
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memory[tid] = cy
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total = in_count - out_count
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label = f"In: {in_count} | Out: {out_count} | Ocupación: {total}"
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# ── devolver en RGB para que Gradio lo muestre bien ─
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annotated_rgb = cv2.cvtColor(annotated, cv2.COLOR_BGR2RGB)
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return annotated_rgb, label
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def reset_counts():
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"""Resetea contador y memoria."""
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global memory, in_count, out_count
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memory, in_count, out_count = {}, 0, 0
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return None, ""
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# ── Interfaz Gradio ────────────────────────────────────
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with gr.Blocks(title="Contador de personas (entrada única)") as demo:
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gr.Markdown("# Contador de personas (entrada única)")
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btn_clear = gr.Button("Limpiar")
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# conectar streaming y botón
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cam.stream(fn=count_people, inputs=[cam], outputs=[out_img, out_lbl])
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btn_clear.click(fn=reset_counts, outputs=[out_img, out_lbl])
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# ── Cola y lanzamiento ─────────────────────────────────
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demo.queue(concurrency_count=2, max_size=60) # 2 hilos, cola máx 60 frames
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demo.launch()
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