github repo: github.com/ximeiorg/ochw
python 推理代码：
def get_labels():
labels = []
with open("data/label.txt", "r", encoding="utf-8") as f:
for line in f:
# line: ! 0
line = line.strip()
label = line.split("\t")[0]
labels.append(label)
return labels
if __name__ == "__main__":
model = HandwritingTrainer.load_from_checkpoint("checkpoint-epoch=32-val_loss=0.156.ckpt")
model.eval()
model = model.to("cuda")
img = Image.open("./testdata/hui.png")
img = img.convert("RGB")
img = img.resize((96,96))
rans = transforms.Compose([
transforms.Resize((96, 96)),
transforms.ToTensor(),
transforms.Normalize(mean=[0.95], std=[0.2])
])
img = trans(img)
img = img.unsqueeze(0)
img = img.to("cuda")
labels = get_labels()
with torch.no_grad():
output = model(img)
output = torch.nn.functional.softmax(output,dim=1)
# 获取top5的预测结果
top5_prob, top5_idx = torch.topk(output, 5)
top5_prob = top5_prob.cpu().numpy()
top5_idx = top5_idx.cpu().numpy()
for i in range(5):
idx = top5_idx[0][i]
print(f"Top {i+1} 预测标签: {labels[idx]}, 概率: {top5_prob[0][i]:.4f}")
得到的结果如下：
Top 1 预测标签: 知, 概率: 0.9505
Top 2 预测标签: 勉, 概率: 0.0095
Top 3 预测标签: 贮, 概率: 0.0025
Top 4 预测标签: 处, 概率: 0.0025
Top 5 预测标签: ‰, 概率: 0.0025