Update app.py

app.py

@@ -1,17 +1,41 @@
 import tensorflow as tf
+
+import math
+import numpy as np
+
 from huggingface_hub import from_pretrained_keras
 import gradio as gr
 
 model = from_pretrained_keras("Dvjc1899/super-resolution")
 
-def infer():
-  return("hello world")
-  
+def infer(img):
+    img = img.resize((300, 300))
+	ycbcr = img.convert("YCbCr")
+    y, cb, cr = ycbcr.split()
+    y = img_to_array(y)
+    y = y.astype("float32") / 255.0
+
+    input = np.expand_dims(y, axis=0)
+    out = model.predict(input)
+
+    out_img_y = out[0]
+    out_img_y *= 255.0
+
+    # Restore the image in RGB color space.
+    out_img_y = out_img_y.clip(0, 255)
+    out_img_y = out_img_y.reshape((np.shape(out_img_y)[0], np.shape(out_img_y)[1]))
+    out_img_y = PIL.Image.fromarray(np.uint8(out_img_y), mode="L")
+    out_img_cb = cb.resize(out_img_y.size, PIL.Image.BICUBIC)
+    out_img_cr = cr.resize(out_img_y.size, PIL.Image.BICUBIC)
+    out_img = PIL.Image.merge("YCbCr", (out_img_y, out_img_cb, out_img_cr)).convert(
+        "RGB"
+    )
+    return out_img
+	
 iface = gr.Interface(
 	fn=infer,
 	title = "Super-resolution",
-	inputs=["text"],
-	outputs=[
-		"textbox",
+	inputs=gr.inputs.Image(label="Input Image"),
+	outputs=[gr.outputs.Image(label="Super-resolution image"),
 	],
 ).launch()