Create app.py

app.py

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+import gradio as gr
+import torch
+from sahi.classification import ImageClassification
+from sahi.utils.cv import visualize_object_predictions, read_image
+from ultralyticsplus import YOLO
+
+def yolov8_inference(
+    image: gr.Image = None,
+    model_path: gr.Dropdown = None,
+    image_size: gr.Slider = 640,
+    conf_threshold: gr.Slider = 0.25,
+    iou_threshold: gr.Slider = 0.45,
+):
+    """
+    YOLOv8 inference function
+    Args:
+        image: Input image
+        model_path: Path to the model
+        image_size: Image size
+        conf_threshold: Confidence threshold
+        iou_threshold: IOU threshold
+    
+    """
+    model = YOLO(model_path)
+    model.overrides['conf'] = conf_threshold
+    model.overrides['iou']= iou_threshold
+    model.overrides['agnostic_nms'] = False  # NMS class-agnostic
+    model.overrides['max_det'] = 1000 
+    
+    # observe results
+    top_class_index = torch.argmax(results[0].probs).item()
+    Class = model.names[top_class_index]
+    print(Class)
+        
+
+inputs = [
+    gr.Image(type="filepath", label="Input Image"),
+    gr.Dropdown(["foduucom/Tyre-Quality-Classification-AI"], 
+                default="foduucom/Tyre-Quality-Classification-AI", label="Model"),
+    gr.Slider(minimum=320, maximum=1280, default=640, step=32, label="Image Size"),
+    gr.Slider(minimum=0.0, maximum=1.0, default=0.25, step=0.05, label="Confidence Threshold"),
+    gr.Slider(minimum=0.0, maximum=1.0, default=0.45, step=0.05, label="IOU Threshold"),
+]
+
+outputs = gr.Image(type="filepath", label="Output Image")
+title = "AI-Powered Tire Quality Inspection: YOLOv8s Enhanced Classification"
+
+description ="""
+🔥 Unveiling ThermalFoduu: Spot Objects with Thermal Vision! 🔍📸 Lost your keys in the dark? 🗝️🌑 ThermalFoduu's got you covered! Powered by Foduu AI, our app effortlessly detects objects in thermal images. No more blurry blobs – just pinpoint accuracy! 🦅🎯
+Love the thermal world? Give us a thumbs up! 👍 Questions or suggestions? Contact us at info@foduu. Let's decode the thermal universe together! 📧🌡️
+"""
+
+
+🌟 Space Description:"""
+Welcome to our 🤖 AI-Powered Tire Quality Inspection Space – a cutting-edge solution harnessing the capabilities of YOLOv8s to revolutionize 🚗 tire quality control processes.
+"""
+🔍 About This Space: """
+This interactive platform empowers you to classify tires with unparalleled precision, utilizing a fine-tuned YOLOv8s model 🎯 specifically developed for identifying defects in tire manufacturing. By submitting an image of a tire, you can instantly determine whether it meets the rigorous quality standards required in the industry, helping to ensure safety and reliability in automotive products.
+"""
+examples = [['samples/1.jpeg', 'foduucom/thermal-image-object-detection', 640, 0.25, 0.45], ['samples/2.jpg', 'foduucom/thermal-image-object-detection', 640, 0.25, 0.45]]
+demo_app = gr.Interface(
+    fn=yolov8_inference,
+    inputs=inputs,
+    outputs=outputs,
+    title=title,
+    description=description,
+    examples=examples,
+    cache_examples=True,
+    theme='huggingface',
+)
+demo_app.queue().launch(debug=True)