Update app.py

app.py

@@ -5,26 +5,10 @@ import torch
 git_processor_base = AutoProcessor.from_pretrained("microsoft/git-base-coco")
 git_model_base = AutoModelForCausalLM.from_pretrained("microsoft/git-base-coco")
 
-git_processor_large = AutoProcessor.from_pretrained("microsoft/git-large-coco")
-git_model_large = AutoModelForCausalLM.from_pretrained("microsoft/git-large-coco")
-
-blip_processor_base = AutoProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
-blip_model_base = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base")
-
-blip_processor_large = AutoProcessor.from_pretrained("Salesforce/blip-image-captioning-large")
-blip_model_large = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-large")
-
-vitgpt_processor = AutoImageProcessor.from_pretrained("nlpconnect/vit-gpt2-image-captioning")
-vitgpt_model = VisionEncoderDecoderModel.from_pretrained("nlpconnect/vit-gpt2-image-captioning")
-vitgpt_tokenizer = AutoTokenizer.from_pretrained("nlpconnect/vit-gpt2-image-captioning")
-
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
 git_model_base.to(device)
-blip_model_base.to(device)
-git_model_large.to(device)
-blip_model_large.to(device)
-vitgpt_model.to(device)
+
 
 def generate_caption(processor, model, image, tokenizer=None):
     inputs = processor(images=image, return_tensors="pt").to(device)
@@ -42,19 +26,11 @@ def generate_caption(processor, model, image, tokenizer=None):
 def generate_captions(image):
     caption_git_base = generate_caption(git_processor_base, git_model_base, image)
 
-    caption_git_large = generate_caption(git_processor_large, git_model_large, image)
-
-    caption_blip_base = generate_caption(blip_processor_base, blip_model_base, image)
-
-    caption_blip_large = generate_caption(blip_processor_large, blip_model_large, image)
-
-    caption_vitgpt = generate_caption(vitgpt_processor, vitgpt_model, image, vitgpt_tokenizer)
-
-    return caption_git_base, caption_git_large, caption_blip_base, caption_blip_large, caption_vitgpt
+    return caption_git_base
 
    
 examples = [["test-1.jpeg"], ["test-2.jpeg"], ["test-3.jpeg"], ["test-4.jpeg"], ["test-5.jpeg"], ["test-6.jpg"]]
-outputs = [gr.outputs.Textbox(label="Caption generated by GIT-base"), gr.outputs.Textbox(label="Caption generated by GIT-large"), gr.outputs.Textbox(label="Caption generated by BLIP-base"), gr.outputs.Textbox(label="Caption generated by BLIP-large"), gr.outputs.Textbox(label="Caption generated by ViT+GPT-2")] 
+outputs = [gr.outputs.Textbox(label="Caption generated by GIT-base")] 
 
 
 interface = gr.Interface(fn=generate_captions,