Why isn't the image appearing on my Flask app with YOLOV5 model after clicking upload?

Question

I'm trying to build an app that can detect cavities in oral images using the YOLOV5 algorithm. I have an error when the user clicks upload it doesn't show the image in the browser, however, I can see the image saved in my app.

I tried tO print the image url and i get "Image URL: /static//static/1685369990.0033317.jpg", Which is a wrong path the image should be in static/img.jpg

This is my app.py code:

import io
import os
import time
import torch
from PIL import Image, ImageDraw, ImageFont
from flask import Flask, jsonify, url_for, render_template, request, redirect

app = Flask(__name__, static_url_path='/static')

RESULT_FOLDER = os.path.join('static')
app.config['RESULT_FOLDER'] = RESULT_FOLDER

model = torch.hub.load('ultralytics/yolov5', 'custom', path='./best.pt')
model.eval()


def draw_boxes(image, boxes, labels):
    draw = ImageDraw.Draw(image)
    font = ImageFont.truetype("arial.ttf", size=12)
    
    for box, label in zip(boxes, labels):
        x1, y1, x2, y2, _, cls = box.tolist()
        draw.rectangle([x1, y1, x2, y2], outline='red', width=2)
        
        text = f'{label}: {int(cls)}'
        text_width, text_height = font.getsize(text)
        draw.rectangle([x1, y1 - text_height, x1 + text_width, y1], fill='red')
        draw.text((x1, y1 - text_height), text, fill='white', font=font)
        
    return image


def get_prediction(img_bytes):
    img = Image.open(io.BytesIO(img_bytes))
    imgs = [img]  # batched list of images

    # Inference
    results = model(imgs, size=640)  # includes NMS
    boxes = results.xyxy[0]  # Get bounding boxes
    labels = results.names[0]  # Get class labels
    
    # Draw bounding boxes and labels on the original image
    img_with_boxes = draw_boxes(img, boxes, labels)

    return img_with_boxes, boxes


@app.route('/', methods=['GET', 'POST'])
def predict():
    if request.method == 'POST':
        if 'file' not in request.files:
            return redirect(request.url)
        file = request.files.get('file')
        if not file:
            return

        img_bytes = file.read()

        try:
            img_with_boxes, boxes = get_prediction(img_bytes)

            img_name = str(time.time()) + '.jpg'
            img_path = os.path.join(app.config['RESULT_FOLDER'], img_name)

            img_with_boxes.save(img_path)
            
            #image_url = '/' + img_path

            image_url = url_for('static', filename=img_name)
            print("Image URL:", image_url)

            return render_template('test.html', result_image= image_url)


        except Exception as e:
            print(str(e))  # Print the exception for debugging
            return render_template('error.html', error=str(e))

    return render_template('index.html')


if __name__ == '__main__':
    app.run(debug=True)