AI-Naga/Container_Code_Detection

1import gradio as gr2from gradio.outputs import Label3import cv24import requests5import os6import numpy as np7 8from ultralytics import YOLO9import yolov510 11# Function for inference12def yolov5_inference(13    image: gr.inputs.Image = None,14    model_path: gr.inputs.Dropdown = None,15    image_size: gr.inputs.Slider = 640,16    conf_threshold: gr.inputs.Slider = 0.25,17    iou_threshold: gr.inputs.Slider = 0.45 ):18 19    # Loading Yolo V5 model20    model = yolov5.load(model_path, device="cpu")21 22    # Setting model configuration 23    model.conf = conf_threshold24    model.iou = iou_threshold25 26    # Inference27    results = model([image], size=image_size)28 29    # Cropping the predictions    30    crops = results.crop(save=False)31    img_crops = []32    for i in range(len(crops)):33        img_crops.append(crops[i]["im"][..., ::-1])34    return results.render()[0], img_crops35        36# gradio Input37inputs = [38    gr.inputs.Image(type="pil", label="Input Image"),39    gr.inputs.Dropdown(["Container_YOLOV5.pt"], label="Model", default = 'Container_YOLOV5.pt'),40    gr.inputs.Slider(minimum=320, maximum=1280, default=640, step=32, label="Image Size"),41    gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.25, step=0.05, label="Confidence Threshold"),42    gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.45, step=0.05, label="IOU Threshold"),43]44 45# gradio Output46outputs = gr.outputs.Image(type="filepath", label="Output Image")47outputs_crops = gr.Gallery(label="Object crop")48 49title = "Container code detection"50 51# gradio examples: "Image", "Model", "Image Size", "Confidence Threshold", "IOU Threshold"52examples = [['image_0.jpg', 'Container_YOLOV5.pt', 640, 0.35, 0.45]53           ,['image_1.jpg', 'Container_YOLOV5.pt', 640, 0.35, 0.45]54           ,['image_2.jpg', 'Container_YOLOV5.pt', 640, 0.35, 0.45],55           ]56 57# gradio app launch58demo_app = gr.Interface(59    fn=yolov5_inference,60    inputs=inputs,61    outputs=[outputs,outputs_crops],62    title=title,63    description="Scroll down for sample inputs !!!",64    examples=examples,65    cache_examples=False,66    live=True,67    theme='huggingface',68)69demo_app.launch(debug=True, enable_queue=True, width=50, height=50)