import gradio as gr
from huggingface_hub import hf_hub_download
from ultralytics import YOLO
import cv2
import numpy as np
import easyocr

# Lade das Modell
model_path = hf_hub_download(repo_id="foduucom/stockmarket-pattern-detection-yolov8", filename="model.pt")
model = YOLO(model_path)

# OCR für Preise
reader = easyocr.Reader(['en'])

def analyze_image(image, prompt):
    # Konvertiere PIL-Bild zu OpenCV-Format
    image_np = np.array(image)
    image_cv = cv2.cvtColor(image_np, cv2.COLOR_RGB2BGR)

    # Führe Objekterkennung durch
    results = model.predict(source=image_np, save=False)

    # Extrahiere Kerzen
    detections = []
    for result in results:
        for box in result.boxes:
            label = result.names[int(box.cls)]
            confidence = float(box.conf)
            xmin, ymin, xmax, ymax = box.xyxy[0].tolist()

            # Extrahiere Farbe
            candle_roi = image_cv[int(ymin):int(ymax), int(xmin):int(xmax)]
            mean_color = np.mean(candle_roi, axis=(0, 1)).astype(int)
            color_rgb = f"RGB({mean_color[2]},{mean_color[1]},{mean_color[0]})"

            # OCR für Opening/Close-Preise (aus Achsen, anpassen an Chart)
            price_text = reader.readtext(image_cv[int(ymin):int(ymax), int(xmin):int(xmax)], detail=0)
            prices = ' '.join(price_text) if price_text else "No price detected"

            detections.append({
                "pattern": label,
                "confidence": confidence,
                "color": color_rgb,
                "prices": prices,
                "x_center": (xmin + xmax) / 2
            })

    # Sortiere nach x-Position (rechts nach links = neueste Kerzen)
    detections = sorted(detections, key=lambda x: x["x_center"], reverse=True)

    # Begrenze auf die letzten 8 Kerzen
    if "last 8 candles" in prompt.lower() or "letzte 8 kerzen" in prompt.lower():
        detections = detections[:8]

    return detections

iface = gr.Interface(
    fn=analyze_image,
    inputs=[
        gr.Image(type="pil", label="Upload TradingView Screenshot"),
        gr.Textbox(label="Prompt", placeholder="Enter your prompt, e.g., 'List last 8 candles with their colors'")
    ],
    outputs="json",
    title="Stock Chart Analysis",
    description="Upload a screenshot and provide a prompt to analyze candlesticks."
)

iface.launch()