| import gradio as gr |
| from Backend.BrandRecognition.Static.Brand_Count_Img import detect_grocery_items |
| from Backend.BrandRecognition.Static.Brand_Count_Img import batch_detect_grocery_items |
|
|
| |
| def create_image_interface(): |
| |
| """ |
| Create an interface for object detection in an image. |
| |
| The interface allows users to upload an image, and the model will return an annotated image, item quantities, and average confidence scores. |
| |
| Parameters |
| ---------- |
| None |
| |
| Returns |
| ------- |
| gr.Interface |
| An Interface object that can be launched to accept user input. |
| |
| """ |
| return gr.Interface( |
| fn=detect_grocery_items, |
| inputs=gr.Image(label="Upload Image", height=400, width=400), |
| outputs=[ |
| gr.Image(label="Image with Bounding Boxes", height=400, width=400), |
| gr.Dataframe(headers=["Item", "Quantity", "Avg Confidence"], label="Detected Items and Quantities", elem_id="summary_table"), |
| gr.Textbox(label="Status", elem_id="status_message") |
| ], |
| title="Grocery Item Detection in an Image", |
| description="Upload an image for object detection. The model will return an annotated image, item quantities, and average confidence scores.", |
| css=".gr-table { font-size: 16px; text-align: left; width: 50%; margin: auto; } #summary_table { margin-top: 20px; }" |
| ) |
|
|
