Added imference time display

yolo-inference-project/src/app.py

@@ -2,17 +2,9 @@ import gradio as gr
 import os
 from model import load_model, perform_inference
 from utils import draw_bounding_boxes
-
-def inference(image, model_name, conf_thresh):
-    if not model_name:
-        raise gr.Error("No model selected. Please select a model.")
-    if not image:
-        raise gr.Error("No image provided. Please upload an image.")
-    
-    model = load_model("models/" + model_name)
-    results = perform_inference(model, image)
-    output_image = draw_bounding_boxes(results, conf_thresh)
-    return output_image
+import time
+import subprocess
+import re
 
 def get_model_names():
     model_dir = "models"  # Update this path to your models directory
@@ -26,6 +18,31 @@ image_paths= [['examples/smaller_many_cans.jpg', 'yolo11m.pt', 0.5],
               ['examples/real_plank.jpg', 'yolo11m.pt', 0.5],
               ]
 
+def inference(image, model_name, conf_thresh):
+    if not model_name:
+        raise gr.Error("No model selected. Please select a model.")
+    if not image:
+        raise gr.Error("No image provided. Please upload an image.")
+    
+    model = load_model("models/" + model_name)
+    results = perform_inference(model, image)
+    output_image = draw_bounding_boxes(results, conf_thresh)
+    speed = results[0].speed
+    speed_str = "Speed: {:.1f}ms preprocess, {:.1f}ms inference, {:.1f}ms postprocess per image".format(
+                    *tuple(speed.values()))
+    speed_str += "\nTotal : {:.1f}ms".format(sum(speed.values()))
+    command = "cat /proc/cpuinfo"
+    
+    all_info = subprocess.check_output(command, shell=True).decode().strip()
+    for line in all_info.split("\n"):
+        if "model name" in line:
+            proc_name = re.sub( ".*model name.*:", "", line,1)    
+            speed_str += "\nRunning on '" + proc_name + "'"
+            break
+
+    print(speed)
+    return output_image,speed_str
+
 demo = gr.Interface(
     fn=inference,
     inputs=[
@@ -33,11 +50,14 @@ demo = gr.Interface(
         gr.Dropdown(choices=model_names, label="Select Model"),
         gr.Slider(minimum=0, maximum=1, step=0.01, value=0.5, label="Confidence Threshold")
     ],
-    outputs=gr.Image(type="numpy", label="Output Image"),
+    outputs=[
+        gr.Image(type="numpy", label="Output Image"),
+        gr.Textbox(label="Inference Time")
+    ],
     title="YOLO Model Inference",
     description="Select a YOLO model, upload an image, and set the confidence threshold to perform inference.",
     examples=image_paths,
-   #     flagging_mode="auto"
+    # flagging_mode="auto"
 )
 
 demo.launch()