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  1. image_feature.py +6 -3
image_feature.py CHANGED
@@ -55,8 +55,8 @@ DEVICE = torch.device('cpu')
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  # model = AutoModel.from_pretrained("google/vit-base-patch16-224-in21k").to(DEVICE)
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  # processor = AutoImageProcessor.from_pretrained("chanhua/autotrain-izefx-v3qh0")
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  # model = AutoModel.from_pretrained("chanhua/autotrain-izefx-v3qh0").to(DEVICE)
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- processor = ViTImageProcessor.from_pretrained('google/vit-large-patch16-224-in21k')
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- model = ViTModel.from_pretrained('google/vit-large-patch16-224-in21k')
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  # processor = ViTImageProcessor.from_pretrained('google/vit-base-patch16-224-in21k')
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  # model = ViTModel.from_pretrained('google/vit-base-patch16-224-in21k')
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@@ -66,12 +66,13 @@ model = ViTModel.from_pretrained('google/vit-large-patch16-224-in21k')
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  # pipe = pipeline(task="image-feature-extraction", model_name="google/vit-base-patch16-384", device=DEVICE, pool=True)
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  # pipe = pipeline(task="image-feature-extraction", model_name="chanhua/autotrain-izefx-v3qh0", device=DEVICE, pool=True)
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  # pipe = pipeline(task="image-feature-extraction", model_name="google/vit-base-patch16-224", device=DEVICE, pool=True, revision="29e7a1e183")
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- pipe = pipeline(task="image-feature-extraction", model_name="google/vit-base-patch16-224-in21k", device=DEVICE, pool=True)
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  # ζŽ¨η†
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  def infer4(url1, url2):
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  try:
 
 
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  print("θΏ›ε…₯ζŽ¨η†")
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  print("打开图片1")
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  # image_real = Image.open(requests.get(url1, stream=True).raw).convert("RGB")
@@ -105,6 +106,8 @@ def infer4(url1, url2):
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  # ζŽ¨η†
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  def infer2(url):
 
 
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  # image_real = Image.open(requests.get(img_urls[0], stream=True).raw).convert("RGB")
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  # image = Image.open(requests.get(url, stream=True).raw).convert("RGB")
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  image = Image.open(url).convert('RGB')
 
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  # model = AutoModel.from_pretrained("google/vit-base-patch16-224-in21k").to(DEVICE)
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  # processor = AutoImageProcessor.from_pretrained("chanhua/autotrain-izefx-v3qh0")
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  # model = AutoModel.from_pretrained("chanhua/autotrain-izefx-v3qh0").to(DEVICE)
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+ # processor = ViTImageProcessor.from_pretrained('google/vit-large-patch16-224-in21k')
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+ # model = ViTModel.from_pretrained('google/vit-large-patch16-224-in21k')
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  # processor = ViTImageProcessor.from_pretrained('google/vit-base-patch16-224-in21k')
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  # model = ViTModel.from_pretrained('google/vit-base-patch16-224-in21k')
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  # pipe = pipeline(task="image-feature-extraction", model_name="google/vit-base-patch16-384", device=DEVICE, pool=True)
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  # pipe = pipeline(task="image-feature-extraction", model_name="chanhua/autotrain-izefx-v3qh0", device=DEVICE, pool=True)
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  # pipe = pipeline(task="image-feature-extraction", model_name="google/vit-base-patch16-224", device=DEVICE, pool=True, revision="29e7a1e183")
 
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  # ζŽ¨η†
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  def infer4(url1, url2):
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  try:
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+ pipe = pipeline(task="image-feature-extraction", model_name="google/vit-base-patch16-224-in21k", device=DEVICE, pool=True)
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+
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  print("θΏ›ε…₯ζŽ¨η†")
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  print("打开图片1")
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  # image_real = Image.open(requests.get(url1, stream=True).raw).convert("RGB")
 
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  # ζŽ¨η†
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  def infer2(url):
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+ processor = AutoImageProcessor.from_pretrained('google/vit-large-patch16-224-in21k')
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+ model = ViTModel.from_pretrained('google/vit-large-patch16-224-in21k')
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  # image_real = Image.open(requests.get(img_urls[0], stream=True).raw).convert("RGB")
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  # image = Image.open(requests.get(url, stream=True).raw).convert("RGB")
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  image = Image.open(url).convert('RGB')