Delete app.py

app.py

@@ -1,39 +0,0 @@
-import torch 
-import re 
-import gradio as gr
-from gradio.components import Image, Textbox
-from transformers import AutoTokenizer, ViTImageProcessor, VisionEncoderDecoderModel 
-
-device=torch.device("cuda" if torch.cuda.is_available() else "cpu")
-local_path = "/app/model/nlpconnect_vit-gpt2-image-captioning/"
-feature_extractor = ViTImageProcessor.from_pretrained(local_path)
-tokenizer = AutoTokenizer.from_pretrained(local_path)
-model = VisionEncoderDecoderModel.from_pretrained(local_path).to(device)
-
-gen_kwargs = {"max_length": 128, "num_beams": 8}
-def predict(image):
-    image = image.convert('RGB')
-    image = feature_extractor(image, return_tensors="pt").pixel_values.to(device)
-    clean_text = lambda x: x.replace('<|endoftext|>','').split('\n')[0]
-    caption_ids = model.generate(image, **gen_kwargs)[0]
-    caption_text = clean_text(tokenizer.decode(caption_ids))
-    return caption_text 
-
-
-_input = Image(label="Upload any Image", type = 'pil')
-_output = Textbox(type="text",label="Captions")
-examples = [f"example{i}.jpg" for i in range(1,7)]
-
-title = "Image Captioning "
-description = "Made by : 炼丹侠"
-iface = gr.Interface(
-            
-        fn=predict,
-        description=description,
-        inputs=_input,
-        outputs=_output,
-        title=title,
-        examples = examples
-    )
-gr.close_all() #关闭所有正在运行的端口
-iface.launch(server_name="0.0.0.0", server_port=7860, debug=True)