neon-tree-resnet18-genus

from deepforest import CropModel

# Load model
model = CropModel.load_model("ritesh313/neon-tree-resnet18-genus")

# Use with DeepForest predictions
# (after running detection with main DeepForest model)
results = model.predict(image_crops)

import torch
from safetensors.torch import load_file
from torchvision import transforms

# Load model weights
state_dict = load_file("model.safetensors")

# Load config for label mapping
import json
with open("config.json") as f:
    config = json.load(f)

# Create your model architecture and load weights
# model.load_state_dict(state_dict)

# Preprocessing
preprocess = transforms.Compose([
    transforms.Resize((224, 224)),
    transforms.ToTensor(),
    transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
])