Upload 8 files

best.onnx

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+version https://git-lfs.github.com/spec/v1
+oid sha256:aba8c963ab3a16b2fe42b8b66f181a1d4cadce9ea91c9b8605e06f3696ba879a
+size 174692170

best_metadata.json

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+{"task": "object-detection", "model_type": "yolov8", "num_classes": 1, "class_names": ["face"]}

config.json

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+{
+    "model_type": "yolov8",
+    "classes": ["face"],
+    "id2label": { "0": "face" },
+    "label2id": { "face": 0 },
+    "inference_config": {
+        "confidence_threshold": 0.5,
+        "iou_threshold": 0.45,
+        "input_size": [640, 640]
+    },
+    "model_details": {
+        "framework": "ultralytics",
+        "architecture": "yolov8l",
+        "num_classes": 1,
+        "input_channels": 3
+    }
+}

data.yaml

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+train: /home/park-ubuntu/mj/data/images/train
+val: /home/park-ubuntu/mj/data/images/val
+
+nc: 1
+names:
+  - face

function.yaml

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+metadata:
+  name: yolov8-function
+  namespace: nuclio
+
+spec:
+  runtime: "python:3.9"
+  handler: "main:handler"
+  description: "YOLOv8 object detection"
+  resources:
+    limits:
+      cpu: "500m"
+      memory: "512Mi"
+  build:
+    path: "./"
+    baseImage: "python:3.9"
+    commands:
+      - pip install -r requirements.txt
+  triggers:
+    myHttpTrigger:
+      class: "http"
+      kind: "http"
+      maxWorkers: 4
+      attributes:
+        port: 8080

model_index.json

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+{
+    "model_type": "object-detection",
+    "architecture": "yolov8",
+    "num_classes": 1,
+    "class_names": ["face"],
+    "input_size": [640, 640],
+    "confidence_threshold": 0.5
+}

requirements.txt

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+torch>=1.7.0
+ultralytics
+numpy
+opencv-python
+flask

yolov8l.yaml

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+# Ultralytics YOLO 🚀, GPL-3.0 license
+
+# Parameters
+nc: 1  # number of classes (face)
+depth_multiple: 1.00
+width_multiple: 1.00
+
+# YOLOv8.0l backbone
+backbone:
+  # [from, repeats, module, args]
+  - [-1, 1, Conv, [64, 3, 2]]  # 0-P1/2
+  - [-1, 1, Conv, [128, 3, 2]]  # 1-P2/4
+  - [-1, 3, C2f, [128, True]]
+  - [-1, 1, Conv, [256, 3, 2]]  # 3-P3/8
+  - [-1, 6, C2f, [256, True]]
+  - [-1, 1, Conv, [512, 3, 2]]  # 5-P4/16
+  - [-1, 6, C2f, [512, True]]
+  - [-1, 1, Conv, [512, 3, 2]]  # 7-P5/32
+  - [-1, 3, C2f, [512, True]]
+  - [-1, 1, SPPF, [512, 5]]  # 9
+
+# YOLOv8.0l head
+head:
+  - [-1, 1, nn.Upsample, [None, 2, 'nearest']]
+  - [[-1, 6], 1, Concat, [1]]  # cat backbone P4
+  - [-1, 3, C2f, [512]]  # 13
+
+  - [-1, 1, nn.Upsample, [None, 2, 'nearest']]
+  - [[-1, 4], 1, Concat, [1]]  # cat backbone P3
+  - [-1, 3, C2f, [256]]  # 17 (P3/8-small)
+
+  - [-1, 1, Conv, [256, 3, 2]]
+  - [[-1, 12], 1, Concat, [1]]  # cat head P4
+  - [-1, 3, C2f, [512]]  # 20 (P4/16-medium)
+
+  - [-1, 1, Conv, [512, 3, 2]]
+  - [[-1, 9], 1, Concat, [1]]  # cat head P5
+  - [-1, 3, C2f, [512]]  # 23 (P5/32-large)
+
+  - [[15, 18, 21], 1, Detect, [nc]]  # Detect(P3, P4, P5)