demo.py

import gradio as gr
import requests
from PIL import Image
import io
import cv2
import numpy as np

fire_count = 0
def plot_one_box(x, img, color=None, label=None, score=None, line_thickness=3):
	# Plots one bounding box on image img
    tl = line_thickness or round(0.002 * (img.shape[0] + img.shape[1]) / 2) + 1  # line/font thickness
    color = color
    c1, c2 = (int(x[0]), int(x[1])), (int(x[2])+int(x[0]), int(x[3])+int(x[1]))
    cv2.rectangle(img, c1, c2, color, thickness=tl, lineType=cv2.LINE_AA)
    if label:
        tf = max(tl - 1, 1)  # font thickness
        t_size = cv2.getTextSize(label, 0, fontScale=tl / 3, thickness=tf)[0]
        c2 = c1[0] + t_size[0], c1[1] - t_size[1] - 3
        cv2.rectangle(img, c1, c2, color, -1, cv2.LINE_AA)  # filled
        cv2.putText(img, label, (c1[0], c1[1] - 2), 0, tl / 3, [0, 0, 0], thickness=tf, lineType=cv2.LINE_AA)

        pro = f"{score:.3f}"
        t_size = cv2.getTextSize(pro, 0, fontScale=tl / 3, thickness=tf)[0]
        c1 = c2
        c2 = c1[0] + t_size[0], c1[1] + t_size[1] + 3
        cv2.rectangle(img, c1, c2, [0, 255, 255], -1, cv2.LINE_AA)  # filled
        cv2.putText(img, pro, (c1[0], c2[1] - 2), 0, tl / 3, [0, 0, 0], thickness=tf, lineType=cv2.LINE_AA)
    return img
    
def fire(frame):
    global fire_count
    
    fire_count = fire_count + 1
    print("fire_count", fire_count) 
    url = "http://127.0.0.1:8080/fire"
    file = {'file': open(frame, 'rb')}

    r = requests.post(url=url, files=file)
   
    fire_output = None
    result = r.json().get('result')
    object_name = r.json().get('class')
    box = r.json().get('coordinate')
    pro = r.json().get('score')
    # print("\n number: ", plate_number)
    # print("\n coordinate: ", box)
    # print("\n score: ", pro)
    try:
        image = cv2.imread(frame, cv2.IMREAD_COLOR)
        if image is None:
            print('image is null')
            sys.exit()
        # image = cv2.resize(image, (1024, 640))
        for obj_name in object_name:
            # print(plate_number)
            if object_name[obj_name]:
                if object_name[obj_name] == "fire":
                    image = plot_one_box(box[obj_name], image, label=object_name[obj_name], score=pro[obj_name], color=[0, 255, 0], line_thickness=1)
                else:
                    image = plot_one_box(box[obj_name], image, label=object_name[obj_name], score=pro[obj_name], color=[0, 0, 255], line_thickness=1)
        image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
        
        fire_output = image.copy()
        
    except:
        pass

    return fire_output
    
with gr.Blocks() as demo:
    gr.Markdown(
        """
    # KBY-AI Fire/Smoke Detection SDK Demo
    We offer SDKs for face recognition, liveness detection(anti-spoofing), ID card recognition and ID document liveness detection. 
    We also specialize in providing outsourcing services with a variety of technical stacks like AI(Computer Vision/Machine Learning), mobile apps, and web apps.
    
    ##### KYC Verification Demo - https://github.com/kby-ai/KYC-Verification-Demo-Android
    ##### ID Capture Web Demo - https://cap.kby-ai.com
    """
    )

    with gr.TabItem("Fire/Smoke Detection"):
        gr.Markdown(
            """
        ##### Docker Hub - https://hub.docker.com/r/kbyai/fire-smoke-detection
        ```bash
        sudo docker pull kbyai/fire-smoke-detection:latest
        sudo docker run -v ./license.txt:/home/openvino/kby-ai-fire/license.txt -p 8081:8080 -p 9001:9000 kbyai/fire-smoke-detection:latest
        ```
        """
        )
        with gr.Row():
            with gr.Column():
                fire_image_input = gr.Image(type='filepath', height=300)
                gr.Examples(['fire_examples/test1.jpg', 'fire_examples/test2.jpg', 'fire_examples/test3.jpg', 'fire_examples/test4.jpg'], 
                            inputs=fire_image_input)
                fire_confirmation_button = gr.Button("Confirm")
            with gr.Column():
                fire_output = gr.Image(type="numpy")

        fire_confirmation_button.click(fire, inputs=fire_image_input, outputs=fire_output)
    gr.HTML('<a href="https://visitorbadge.io/status?path=https%3A%2F%2Fweb.kby-ai.com%2F"><img src="https://api.visitorbadge.io/api/combined?path=https%3A%2F%2Fweb.kby-ai.com%2F&label=VISITORS&countColor=%23263759" /></a>')

demo.launch(server_name="0.0.0.0", server_port=7860)