Upload exampleDetection.py

exampleDetection.py

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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}")