# app.py
import cv2
import gradio as gr
from ultralytics import YOLO

# ── Config ─────────────────────────────────────────────
MODEL_PATH = "yolov8n.pt"     # peso pre-entrenado (COCO)
CONF_THRES = 0.3              # confianza mínima
LINE_RATIO = 0.5              # línea virtual: mitad de la altura
# ───────────────────────────────────────────────────────

model = YOLO(MODEL_PATH)

# Estado global
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 ByteTrack interno
    results = model.track(frame, classes=[0], conf=CONF_THRES,
                          persist=True, verbose=False)  # solo clase “person”

    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

            # 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)

            # 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

    # Overlay de números
    total = in_count - out_count
    label = f"In: {in_count} | Out: {out_count} | Ocupación: {total}"
    cv2.putText(annotated, label, (10, 30),
                cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 2)

    return annotated, label


demo = gr.Interface(
    fn=count_people,
    inputs=gr.Image(source="webcam", streaming=True),
    outputs=[gr.Image(), gr.Text()],
    title="Contador de personas (entrada única)",
    live=True,
)

if __name__ == "__main__":
    demo.launch()