from fastapi import FastAPI, File, UploadFile
import io
import numpy as np
from PIL import Image
import uvicorn
import cv2
from fastdepth import FastDepth
model = FastDepth(pretrained=True)
model.eval()
app = FastAPI()

def analyzepath(image):
    depth_map = model(image).squeeze().cpu().numpy()
    return detect_path(depth_map)  # Xử lý đường đi nhanh hơn
@app.post("/analyze_path/")
async def analyze_path(file: UploadFile = File(...)):
    image_bytes = await file.read()
    image = Image.open(io.BytesIO(image_bytes)).convert("L")  # Chuyển ảnh sang grayscale
    mImage = cv2.flip(image, -1)
    #depth_map = np.array(image)
    depth_map = analyzepath(mImage)
    
    # Phân tích ảnh Depth Map
    command = detect_path(flipped_depth_map)

    return {"command": command}

def detect_path(depth_map):
    _, thresh = cv2.threshold(depth_map, 200, 255, cv2.THRESH_BINARY)
    contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

    if len(contours) == 0:
        return "forward"
    
    left_region = np.mean(depth_map[:, :depth_map.shape[1]//3])
    right_region = np.mean(depth_map[:, 2*depth_map.shape[1]//3:])
    
    if left_region > right_region:
        return "left"
    else:
        return "right"