Delete app.py

app.py

@@ -1,42 +0,0 @@
-import gradio
-from transformers import ViltProcessor, ViltForQuestionAnswering
-from PIL import Image
-
-processor = ViltProcessor.from_pretrained("vilt-b32-finetuned-vqa")
-model = ViltForQuestionAnswering.from_pretrained("vilt-b32-finetuned-vqa")
-
-
-def predict_answer(image, question):
-    image = Image.fromarray(image.astype('uint8'), 'RGB')
-    encoding = processor(image, question, return_tensors="pt")
-    outputs = model(**encoding)
-    logits = outputs.logits
-    probs = logits.softmax(dim=-1)
-    sorted_probs, sorted_indices = probs[0].sort(descending=True)
-    answer_list = []
-    for i in range(5):
-        prob = sorted_probs[i].item()
-        if prob > 0.00:
-            idx = sorted_indices[i].item()
-            answer = model.config.id2label[idx]
-            answer_list.append(f"{answer}: {prob:.2%}")
-    return answer_list
-
-
-inputs = [
-    gradio.components.Image(label="Image"),
-    gradio.components.Textbox(label="Question", placeholder="Enter your question here.")
-]
-
-outputs = [
-    gradio.components.Textbox(label="Answer 1"),
-    gradio.components.Textbox(label="Answer 2"),
-    gradio.components.Textbox(label="Answer 3"),
-    gradio.components.Textbox(label="Answer 4"),
-    gradio.components.Textbox(label="Answer 5")
-]
-
-title = "Visual Question Answering (vilt-b32-finetuned-vqa)"
-
-gradio.Interface(fn=predict_answer, inputs=inputs, outputs=outputs, title=title, allow_flagging="never",
-                 css="footer{display:none !important}").launch()