Upload YOLOv8l model

config.json

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+{
+  "model_type": "yolov8",
+  "scale": "l",
+  "num_classes": 80,
+  "image_size": [
+    640,
+    640
+  ],
+  "confidence_threshold": 0.25,
+  "iou_threshold": 0.45,
+  "max_detections": 300,
+  "backbone_type": "default",
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
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+  },
+  "label2id": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
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+  },
+  "architectures": [
+    "YoloDetectionModel"
+  ]
+}

example.py

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+
+# Example script for using the yolov8_l model from Hugging Face
+import torch
+import cv2
+import numpy as np
+from PIL import Image
+from transformers import AutoImageProcessor, AutoModelForObjectDetection
+
+# Load model and processor
+model = AutoModelForObjectDetection.from_pretrained("lkk688/yolov8l-model")
+processor = AutoImageProcessor.from_pretrained("lkk688/yolov8l-model")
+
+# Function to run inference on an image
+def detect_objects(image_path, confidence_threshold=0.25):
+    # Load image
+    image = Image.open(image_path).convert("RGB")
+    
+    # Process image
+    inputs = processor(images=image, return_tensors="pt")
+    
+    # Run inference
+    with torch.no_grad():
+        outputs = model(**inputs)
+    
+    # Post-process outputs
+    target_sizes = torch.tensor([image.size[::-1]])
+    results = processor.post_process_object_detection(
+        outputs, 
+        threshold=confidence_threshold,
+        target_sizes=target_sizes
+    )[0]
+    
+    # Print results
+    for score, label, box in zip(results["scores"], results["labels"], results["boxes"]):
+        box = [round(i, 2) for i in box.tolist()]
+        print(
+            f"Detected {model.config.id2label[label.item()]} with confidence "
+            f"{round(score.item(), 3)} at location {box}"
+        )
+    
+    return results
+
+# Example usage
+if __name__ == "__main__":
+    # Replace with your image path
+    image_path = "path/to/your/image.jpg"
+    detect_objects(image_path)

preprocessor_config.json

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+{
+  "do_normalize": true,
+  "do_resize": true,
+  "do_rescale": true,
+  "image_mean": [
+    0.0,
+    0.0,
+    0.0
+  ],
+  "image_std": [
+    1.0,
+    1.0,
+    1.0
+  ],
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 640,
+    "width": 640
+  },
+  "use_letterbox": true
+}

yolov8_l.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a6e8bdc228932aaf97f4ad3bdd02def49d015c4d811133bfd1e92ffa82617f86
+size 175159011