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Trashscan8m

YOLOv8 mobilemodelpackageyolov8mv2 ONNX model for waste classification.

ArtOtherVersionRevision c76b2b8CBewertung

Modellquelle

Art
Other
Dateigröße
98,8 MB
Version
vRevision c76b2b8
Aktualisiert
16. Sept. 2026
Downloads
0
Quelle
Hugging Face

Quellenbeschreibung

trashscan8m

YOLOv8 mobile_model_package_yolov8m_v2 ONNX model for waste classification.

Classes

IndexClass
0paper
1plastic
2metal
3organic
4other

Usage

import onnxruntime
import numpy as np
from PIL import Image

session = onnxruntime.InferenceSession("best.onnx")
input_name = session.get_inputs()[0].name
# Input: [1, 3, 640, 640] normalized float32
# Output: [1, 9, 8400] = [cx, cy, w, h, p0, p1, p2, p3, p4]

Model Specs

  • Input size: 640x640
  • Format: ONNX
  • Confidence threshold: 0.25
  • IoU threshold: 0.5

Quellen

1 Quelle
Hugging FacePrimärVersion c76b2b85dc3c9d07bc7696578eb0436a3d9e53d0
huggingface.co/ditoow/trashscan8m/tree/c76b2b85dc3c9d07bc7696578eb0436a3d9e53d0

Verifiziert 2. Sept.

Modellartefakte

1 Artefakt

best.onnx

onnx · 98,8 MB · SHA-256 6f3daad199f7…a7d2 · Hugging Face

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Quellenauszüge

2 Auszüge

--- language: en license: mit tags: - yolov8 - object-detection - waste-classification library_name: onnx pipeline_tag: object-detection --- # trashscan8m YOLOv8 mobile_model_package_yolov8m_v2 ONNX model for waste classification. ## Classes | Index | Class | |-------|-------| | 0 | paper | | 1 | plastic | | 2 | metal | | 3 | organic | | 4 | other | ## Usage ```python import onnxruntime import numpy as np from PIL import Image session = onnxruntime.InferenceSession("best.onnx") input_name = session.get_inputs()[0].name # Input: [1, 3, 640, 640] normalized float32 # Output: [1, 9, 8400] = [cx, cy, w, h, p0, p1, p2, p3, p4] ``` ## Model Specs - Input size: 640x640 - Format: ONNX - Confidence threshold: 0.25 - IoU threshold: 0.5

Source context: 0 downloads · 0 likes · Pipeline object-detection · Library onnx · Repo ditoow/trashscan8m