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import torch
import os
from transformers import AutoProcessor
from PIL import Image
model_path = "D:/nighttest/nightshadeblip_high.pth"
test_path = 'D:/nighttest/test/'
model = torch.load(model_path)
processor = AutoProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
model.eval()
for filename in os.listdir(test_path):
file_path = os.path.join(test_path, filename)
if os.path.isfile(file_path):
image = Image.open(file_path)
device = "cuda"
inputs = processor(images=image, return_tensors="pt").to(device)
pixel_values = inputs.pixel_values
generated_ids = model.generate(pixel_values=pixel_values, max_length=50)
generated_caption = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
print(f"[{generated_caption}] {file_path}")
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