Update app.py

app.py

@@ -6,24 +6,24 @@ from PIL import Image
 import matplotlib.pyplot as plt
 
 i1 = gr.inputs.Image(shape=(256, 256))
-i2 = gr.inputs.Slider(minimum=2, maximum=4, step=0.1, default=None, label="Scale for intensity - the more value the less the intensity in the pixels")
+#i2 = gr.inputs.Slider(minimum=2, maximum=4, step=0.1, default=None, label="Scale for intensity - the more value the less the intensity in the pixels")
 o1 = gr.outputs.Image()
 o2 = gr.outputs.Image()
 gen_model = load_model('256_model_250ep.h5')
 
-def colorify(pixels, slider_value):
+def colorify(pixels):
   
   pixels = (pixels - 127.5) / 127.5
   pixels = np.expand_dims(pixels, 0)
   gen_image = gen_model.predict(pixels)
-  gen_image = (gen_image + 1) / (slider_value)
+  gen_image = (gen_image + 1) / 1.8
   
   return Image.fromarray((gen_image[0] * 255.0).astype(np.uint8))
   
 title = "Colorify"
 description = "Recolor your images using this lite version of PIX2PIX GAN , model is trained on 700 randomly collected images from the internet with 256*256 pixels" 
-examples=[['example1.png', 2],['example2.jpg', 2]]
+examples=[['example1.png'],['example2.jpg']]
 article = "<p style='text-align: center'>"
 
-gr.Interface(fn=colorify, inputs=[i1, i2], outputs=o1, title=title, description=description, article=article, examples=examples, enable_queue=True).launch()
+gr.Interface(fn=colorify, inputs=i1, outputs=o1, title=title, description=description, article=article, examples=examples, enable_queue=True).launch()