Film Photo Classification

2. Download model

from huggingface_hub import hf_hub_download

hf_hub_download(repo_id="chr1sggg/Film-Photo-Classification", filename="model.pth")

3. Load Model

import torch
import torchvision

MODEL_PATH = "your_path"
DEVICE = "" #cuda / cpu / mps

model = torchvision.models.resnet18(weights=None)
model.fc = torch.nn.Linear(512, 2)
model.load_state_dict(
  torch.load(MODEL_PATH, map_location=DEVICE)
)

model.to(DEVICE)
model.eval()

--- license: apache-2.0 base_model: - microsoft/resnet-18 pipeline_tag: image-classification --- # Film Photo Classifier This model is built on the ResNet-18 CNN architecture and trained to distinguish film photographs from digital ones by analyzing differences in texture, color rendition, and overall visual characteristics. It designed to capture the subtle traits that make film photography unique, and achieves great classification performance. # Demo # Installation 1. Install libs ``` pip install huggingface_hub pip install torch torchvision ``` 2. Download model ```python from huggingface_hub import hf_hub_download hf_hub_download(repo_id="chr1sggg/Film-Photo-Classification", filename="model.pth") ``` 3. Load Model ```python import torch import torchvision MODEL_PATH = "your_path" DEVICE = "" #cuda / cpu / mps model = torchvision.models.resnet18(weights=None) model.fc = torch.nn.Linear(512, 2) model.load_state_dict( torch.load(MODEL_PATH, map_location=DEVICE) ) model.to(DEVICE) model.eval() ```