city

app.py

@@ -1,5 +1,4 @@
 import gradio as gr
-
 from matplotlib import gridspec
 import matplotlib.pyplot as plt
 import numpy as np
@@ -75,8 +74,9 @@ def draw_plot(pred_img, seg):
     ax.tick_params(width=0.0, labelsize=25)
     return fig
 
-def sepia(input_img):
-    input_img = Image.fromarray(input_img)
+def sepia(input_text):
+    # Load the image using the input text (assumed to be a path to an image)
+    input_img = Image.open(input_text)
 
     inputs = feature_extractor(images=input_img, return_tensors="tf")
     outputs = model(**inputs)
@@ -85,16 +85,15 @@ def sepia(input_img):
     logits = tf.transpose(logits, [0, 2, 3, 1])
     logits = tf.image.resize(
         logits, input_img.size[::-1]
-    )  # We reverse the shape of `image` because `image.size` returns width and height.
+    )
     seg = tf.math.argmax(logits, axis=-1)[0]
 
     color_seg = np.zeros(
         (seg.shape[0], seg.shape[1], 3), dtype=np.uint8
-    )  # height, width, 3
+    )
     for label, color in enumerate(colormap):
         color_seg[seg.numpy() == label, :] = color
 
-    # Show image + mask
     pred_img = np.array(input_img) * 0.5 + color_seg * 0.5
     pred_img = pred_img.astype(np.uint8)
 
@@ -102,11 +101,9 @@ def sepia(input_img):
     return fig
 
 demo = gr.Interface(fn=sepia,
-                    inputs=gr.Textbox(text="Enter text here"),
+                    inputs=gr.Textbox(text="Enter image file path"),
                     outputs=['plot'],
                     examples=["img_1.jpg", "img_2.jpeg", "img_3.jpg", "img_4.jpg", "img_5.png"],
                     allow_flagging='never')
 
-
-
 demo.launch()