Upload app.py

app.py

@@ -0,0 +1,99 @@
+import threading
+
+import gradio as gr
+
+from tools import mtpnet_demo, yolop_demo, yolopv2_demo
+
+
+def Hex_to_RGB(hex_string):
+    # your code here
+    r = int(hex_string[1:3], 16)
+    g = int(hex_string[3:5], 16)
+    b = int(hex_string[5:7], 16)
+    return [r, g, b]
+
+
+class TaskThread(threading.Thread):
+    def __init__(self, func, args=()):
+        super(TaskThread, self).__init__()
+        self.func = func
+        self.args = args
+
+    def run(self):
+        self.result = self.func(*self.args)
+
+    def getResult(self):
+        try:
+            return self.result
+        except Exception:
+            return None
+
+
+def detect(path, model, task, thickness, alpha_da, alpha_ll, color1, color2, color3):
+    global mtpnet, yolop
+    color = [Hex_to_RGB(color1), Hex_to_RGB(color2), Hex_to_RGB(color3)]
+    alpha = [alpha_da, alpha_ll]
+    result, result2, result3 = None, None, None
+    if 'mtpnet' in model:
+        mtpnet = TaskThread(mtpnet_demo.detect, args=(path, task, thickness, color, alpha))
+        mtpnet.start()
+
+    if 'yolop' in model:
+        yolop = TaskThread(yolop_demo.detect, args=(path, task, thickness, color, alpha))
+        yolop.start()
+
+    if 'mtpnet' in model:
+        mtpnet.join()
+        result = mtpnet.getResult()
+
+    if 'yolop' in model:
+        yolop.join()
+        result2 = yolop.getResult()
+
+    # if 'yolopv2' in model:
+    #     yolopv2 = TaskThread(yolopv2_demo.detect, args=(path, task, thickness, color, alpha))
+    #     yolopv2.start()
+    #     yolopv2.join()
+    #     result3 = yolopv2.getResult()
+
+    return result, result2
+
+
+gr.Interface(
+    fn=detect,
+    inputs=
+    [
+        gr.Image(type='filepath', label="Input Image"),
+        gr.CheckboxGroup(["mtpnet", "yolop"], value=["mtpnet", "yolop"], label="Select model"),
+        gr.CheckboxGroup(["Vehicle detection", "Driving area segmentation", "Lane detection"],
+                         value=["Vehicle detection", "Driving area segmentation", "Lane detection"],
+                         label="Select task"),
+        gr.Slider(1, 5, value=2, label="Detection box line thickness", step=1),
+        gr.Slider(0.1, 1, value=0.5, label="Driving area transparency", step=0.1),
+        gr.Slider(0.1, 1, value=1, label="Lane Line area transparency", step=0.1),
+        gr.ColorPicker(label="Detection Box Color", value='#FFFF00'),
+        gr.ColorPicker(label="Driving Area Segmentation Color", value='#00FF00'),
+        gr.ColorPicker(label="Lane Line Color", value='#FF0000')
+    ],
+    outputs=[
+        gr.Image(label="Output image by mtpnet"),
+        # gr.Image(label="Output Image by yolopv2"),
+        gr.Image(label="Output image by yolop")
+        ],
+    title="MtpNet 💪",
+    examples=
+    [
+        ["img/1.jpg", ["mtpnet", "yolop"], ["Vehicle detection", "Driving area segmentation", "Lane detection"], 2, 0.5, 1, '#FFFF00', '#00FF00', '#FF0000'],
+        ["img/12.png", ["mtpnet", "yolop"], ["Vehicle detection", "Driving area segmentation", "Lane detection"], 2, 0.5, 1, '#FFFF00', '#00FF00', '#FF0000'],
+        ["img/2.jpg", ["mtpnet", "yolop"], ["Vehicle detection", "Driving area segmentation", "Lane detection"], 2, 0.5, 1, '#FFFF00', '#00FF00', '#FF0000'],
+        ["img/3.jpg", ["mtpnet", "yolop"], ["Vehicle detection", "Driving area segmentation", "Lane detection"], 2, 0.5, 1, '#FFFF00', '#00FF00', '#FF0000'],
+        ["img/4.jpg", ["mtpnet", "yolop"], ["Vehicle detection", "Driving area segmentation", "Lane detection"], 2, 0.5, 1, '#FFFF00', '#00FF00', '#FF0000'],
+        ["img/5.jpg", ["mtpnet", "yolop"], ["Vehicle detection", "Driving area segmentation", "Lane detection"], 2, 0.5, 1, '#FFFF00', '#00FF00', '#FF0000'],
+        ["img/7.jpg", ["mtpnet", "yolop"], ["Vehicle detection", "Driving area segmentation", "Lane detection"], 2, 0.5, 1, '#FFFF00', '#00FF00', '#FF0000'],
+        ["img/8.jpg", ["mtpnet", "yolop"], ["Vehicle detection", "Driving area segmentation", "Lane detection"], 2, 0.5, 1, '#FFFF00', '#00FF00', '#FF0000'],
+        ["img/10.jpg", ["mtpnet", "yolop"], ["Vehicle detection", "Driving area segmentation", "Lane detection"], 2, 0.5, 1, '#FFFF00', '#00FF00', '#FF0000'],
+        ["img/11.png", ["mtpnet", "yolop"], ["Vehicle detection", "Driving area segmentation", "Lane detection"], 2, 0.5, 1, '#FFFF00', '#00FF00', '#FF0000'],
+
+    ],
+    theme='default',
+    description="MtpNet 💪: demo for multi-task panoptic driving 🚗 perception network").launch(share=False)