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import gradio as gr
import pandas as pd
from ultralytics import YOLO
from datetime import datetime
categories = {
0: "Beans",
1: "Butter",
2: "Cheese",
3: "Drink",
4: "Jogurt",
5: "Milk",
6: "Pasta",
7: "Rice",
8: "Snacks",
9: "Tuna"
}
# inventory_separate_entries = pd.DataFrame(columns=["Product", "Time added"])
inventory_separate_entries = pd.read_excel("file.xlsx", sheet_name='History of entries')
print(inventory_separate_entries)
model = YOLO("../object_detection/runs/detect/train7/weights/best.pt")
def get_value_counts_df(inventory_separate_entries):
value_counts = inventory_separate_entries['Product'].value_counts(dropna=True, sort=True)
df_val_counts = pd.DataFrame(value_counts)
df_value_counts_reset = df_val_counts.reset_index()
df_value_counts_reset.columns = ['Product', 'Quantity']
return df_value_counts_reset
def add_item(item_name):
inventory_separate_entries.loc[-1] = [item_name, datetime.today().strftime('%Y-%m-%d %H:%M:%S')]
inventory_separate_entries.index = inventory_separate_entries.index + 1 # shifting index
inventory_separate_entries.sort_index(inplace=True)
def detect_objects(input_img):
result_img = model([input_img])
print("result", result_img[0].boxes)
detected_categories = []
for r in result_img[0].boxes:
for element in r.data:
detected_category = int(element[-1])
confidence = element[-2]
print(r.data)
detected_categories.append((detected_category, confidence))
print(detected_categories)
sorted_detected_categories = sorted(detected_categories, key=lambda x: x[1], reverse=True)
if len(sorted_detected_categories) > 0:
detected_category = categories[sorted_detected_categories[0][0]]
else:
detected_category = "Nothing detected"
label = gr.Label(detected_category, visible=True)
result_img = result_img[0].plot()
return gr.Image(result_img, visible=True), label#, add_item_btn # detection_interface
def refresh_inventory():
value_counts_df = get_value_counts_df(inventory_separate_entries)
with pd.ExcelWriter("file.xlsx") as writer:
value_counts_df.to_excel(writer, sheet_name='Total inventory', index=False)
inventory_separate_entries.to_excel(writer, sheet_name='History of entries', index=False)
return value_counts_df, inventory_separate_entries
with gr.Blocks() as inventory_interface:
with gr.Row():
refresh_btn = gr.Button("Refresh Inventory")
export_btn = gr.DownloadButton("Export Inventory", value="/file=file.xlsx")
value_counts_df = get_value_counts_df(inventory_separate_entries)
inventory_title = gr.Label("Inventory Summary", color="grey")
inventory_table = gr.DataFrame(value_counts_df)
history_title = gr.Label("History of added items", color="grey")
history_table = gr.DataFrame(inventory_separate_entries)
output_file = gr.File(visible=False)
refresh_btn.click(refresh_inventory, outputs=[inventory_table, history_table])
with gr.Blocks() as scan_interface:
with gr.Row(equal_height=False):
input = gr.Image()
greet_btn = gr.Button("Detect items")
with gr.Row() as row:
output = gr.Image()
with gr.Column():
label = gr.Label("Nothing detected", visible=True)
add_item_btn = gr.Button("Add item", visible=True)
add_item_btn.click(add_item, inputs=label)
greet_btn.click(detect_objects, inputs=input, outputs=[output, label])
demo = gr.TabbedInterface([scan_interface, inventory_interface], ["Scan items", "Inventory"])
demo.launch(share=True, allowed_paths=["file.xlsx"]) |