Update app.py

app.py

@@ -6,7 +6,6 @@ import numpy as np
 from PIL import Image
 import tensorflow as tf
 from transformers import SegformerFeatureExtractor, TFSegformerForSemanticSegmentation
-from tensorflow.keras.applications.resnet50 import ResNet50, preprocess_input, decode_predictions
 
 feature_extractor = SegformerFeatureExtractor.from_pretrained(
     "nvidia/segformer-b0-finetuned-cityscapes-512-1024"
@@ -102,21 +101,12 @@ def sepia(input_img):
     fig = draw_plot(pred_img, seg)
     return fig
 
-    custom_template = "my_custom_template.html"
-model = ResNet50()
-def classify_image(inp):
-    inp = preprocess_input(inp)
-    preds = model.predict(inp)
-    label = decode_predictions(preds, top=1)[0][0][1]
-    return label
-
 
 demo = gr.Interface(fn=sepia,
                     inputs=gr.Image(shape=(400, 600)),
                     outputs=['plot'],
                     title="SWJIN11 TASK",
                     description="경제학과 202211357 진성원",
-                    interpretation="tooltip",
                     examples=["ADE_val_00000001.jpeg", "ADE_val_00001248.jpg", "image1.jpg", "image2.jpg", "image3.jpg", "image4.jpg"],
                     allow_flagging='never')