TuanScientist commited on
Commit
22e17e4
1 Parent(s): eae39b8

Upload 2 files

Browse files
Files changed (2) hide show
  1. calories.xlsx +0 -0
  2. calories_compare.py +73 -0
calories.xlsx ADDED
Binary file (18.1 kB). View file
 
calories_compare.py ADDED
@@ -0,0 +1,73 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import re
2
+ from fuzzywuzzy import fuzz
3
+ import pandas as pd
4
+ import gradio as gr
5
+
6
+ def calculate_total_calories(user_input):
7
+ df_menu = pd.read_excel('calories.xlsx')
8
+
9
+ # Define a regular expression pattern to extract the quantity and item name
10
+ pattern = r'(\d+)\s+(.+)'
11
+
12
+ # Split the user input into individual menu items
13
+ menu_items = user_input.split(',')
14
+
15
+ total_calories = 0
16
+ results = []
17
+
18
+ for item in menu_items:
19
+ # Extract the quantity and item name from each menu item using regular expressions
20
+ match = re.match(pattern, item.strip())
21
+
22
+ if match:
23
+ quantity = int(match.group(1))
24
+ item_name = match.group(2)
25
+ else:
26
+ quantity = 1 # Assume a default quantity of 1 if not specified
27
+ item_name = item.strip()
28
+
29
+ # Calculate the similarity scores between the item name and menu item names
30
+ similarity_scores = df_menu['food'].apply(lambda x: fuzz.token_set_ratio(x.lower(), item_name.lower()))
31
+
32
+ # Find the closest match with the highest similarity score
33
+ closest_match_index = similarity_scores.idxmax()
34
+ closest_match_score = similarity_scores[closest_match_index]
35
+
36
+ # Check if the similarity score is above a certain threshold
37
+ threshold = 60
38
+ if closest_match_score < threshold:
39
+ results.append("Không tìm thấy thông tin thức ăn : " + item_name)
40
+ continue
41
+
42
+ # Get the closest match menu item details
43
+ closest_match = df_menu.loc[closest_match_index]
44
+ menu_name = closest_match['food']
45
+ unit = closest_match['detail']
46
+ calories = closest_match['calo']
47
+
48
+ # Calculate the total calories for the current menu item
49
+ item_calories = calories * quantity
50
+ total_calories += item_calories
51
+ results.append("Tên món ăn : " + menu_name)
52
+ results.append("Số lượng : " + str(quantity))
53
+ results.append("Đơn vị : " + unit)
54
+ results.append("Lượng calories trong mỗi đơn vị : " + str(calories)+ " Kcals")
55
+ results.append("Tổng lượng calories của " + menu_name + " : " + str(item_calories)+ " Kcals")
56
+ results.append("") # Add an empty entry for spacing
57
+
58
+ results.append(str(total_calories) + " Kcals")
59
+ return "\n".join(results[0:-1]) , results[-1]
60
+
61
+ output_text = [
62
+ gr.outputs.Textbox(label="Thông tin các thành phần trong bữa ăn "),
63
+ gr.outputs.Textbox(label="Tổng lượng calories của bữa ăn ")
64
+ ]
65
+
66
+ def gradio_interface():
67
+ input_text = gr.inputs.Textbox(label="Hãy cho tôi biết bữa ăn hôm nay của bạn" )
68
+ gr_interface = gr.Interface(fn=calculate_total_calories, inputs=input_text, outputs=output_text, title="Tính Toán Thực Đơn Hằng Ngày" , examples = ["1 phần cơm tấm sườn bì , 2 trái chuối","1 phần phở bò , 1 phần bánh Flan"])
69
+ return gr_interface
70
+
71
+ if __name__ == "__main__":
72
+ gr_interface = gradio_interface()
73
+ gr_interface.launch()