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best.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:3451eb8f25702d9b96cac26b56888a598ebef203bd3692fee6199c8412b58c38
+size 52035841

inkind_app_2.py

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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"])