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import numpy as np | |
import pandas as pd | |
import gradio as gr | |
from PIL import Image, ImageDraw, ImageFont | |
from io import BytesIO | |
import json | |
import cv2 | |
from ultralytics import YOLO | |
# ======================= МОДЕЛЬ =================================== | |
model = YOLO("yolov11m_best.pt") | |
# ================== ЧТЕНИЕ НАЗВАНИЙ И ЦЕН ======================= | |
with open('Fruit_Veggies_Price.json', 'r', encoding='utf-8') as file: | |
fruits_data = json.load(file) | |
# ===================== ДЕТЕКЦИЯ ПЛОДА ============================ | |
def detect_fruit(image): | |
# считываем изображение | |
# предполагается, что image - это объект PIL Image | |
image_cv = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR) | |
# детекция | |
detections = model.predict(source=image_cv, conf=0.5) | |
# проверка на наличие детекций | |
if len(detections[0].boxes.cls) == 0: | |
return image_cv, None | |
result_np_image = detections[0].plot() | |
result_np_image = cv2.cvtColor(result_np_image, cv2.COLOR_BGR2RGB) | |
detected_fruit = model.names[int(detections[0].boxes.cls[0])] | |
return result_np_image, detected_fruit | |
# =========================== ЧЕК ================================ | |
def create_receipt(detected_fruit, weight): | |
data = fruits_data[detected_fruit] | |
fruit_name = data['name'] | |
price = data['price_per_kg'] | |
total_price = round(price * weight, 2) | |
receipt_img = Image.new("RGB", (300, 200), color="white") | |
draw = ImageDraw.Draw(receipt_img) | |
try: | |
font = ImageFont.truetype("DejaVuSans.ttf", 18) | |
except IOError: | |
font = ImageFont.load_default() | |
draw.text((10, 10), "Чек", fill="black", font=font) | |
draw.text((10, 50), f"Продукт: {fruit_name}", fill="black", font=font) | |
draw.text((10, 80), f"Вес: {weight} кг", fill="black", font=font) | |
draw.text((10, 110), f"Цена за кг: {price} руб.", fill="black", font=font) | |
draw.text((10, 140), f"Сумма: {total_price} руб.", fill="black", font=font) | |
return receipt_img | |
# ======================= ИНТЕРФЕЙС =============================== | |
def gradio_interface(image, weight): | |
if weight <= 0: | |
gr.Info('Укажите вес товара') | |
return None, None | |
result_np_image, detected_fruit = detect_fruit(image) | |
if detected_fruit == None: | |
gr.Info('Не удалось определить товар') | |
return None, None | |
receipt = create_receipt(detected_fruit, weight) | |
return result_np_image, receipt | |
image_input = gr.Image( | |
label="Изображение", | |
width=640, | |
height=380 | |
) | |
weight_input = gr.Number(label="Вес (кг)") | |
image_output = gr.Image( | |
label="Распознанный товар", | |
type="numpy", | |
width=640, | |
height=380 | |
) | |
receipt_output = gr.Image( | |
label="Чек", | |
type="pil", | |
width=400, | |
height=400 | |
) | |
gr.Interface( | |
fn=gradio_interface, | |
inputs=[image_input, weight_input], | |
outputs=[image_output, receipt_output], | |
title="Определение товара и создание чека", | |
description="Загрузите изображение, введите вес и получите чек" | |
).launch() |