Add application files

app.py

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+import tensorflow as tf
+import numpy as np
+from imageio.v2 import imread
+import os, glob, cv2, shutil
+from super_image import EdsrModel, ImageLoader
+from PIL import Image
+import gradio as gr
+
+pb = 'dmt.pb'
+style_dim = 8
+img_size=256
+
+model_scale = EdsrModel.from_pretrained('eugenesiow/edsr-base', scale=2)
+
+def preprocess(img):
+  return (img / 255. - 0.5) * 2
+
+def deprocess(img):
+  return (img + 1) / 2
+
+def load_image(path):
+  img = cv2.resize(imread(path), (img_size, img_size))
+  img_ = np.expand_dims(preprocess(img), 0)
+  return img / 255., img_
+
+def inference(A,B):
+  with tf.Graph().as_default():
+      output_graph_def = tf.compat.v1.GraphDef()
+
+      with open(pb, 'rb') as fr:
+          output_graph_def.ParseFromString(fr.read())
+          tf.import_graph_def(output_graph_def, name='')
+
+      sess = tf.compat.v1.Session()
+      sess.run(tf.compat.v1.global_variables_initializer())
+      graph = tf.compat.v1.get_default_graph()
+      Xs = graph.get_tensor_by_name('decoder_1/g:0')
+      X = graph.get_tensor_by_name('X:0')
+      Y = graph.get_tensor_by_name('Y:0')
+  print("1")
+  A_img, A_img_ = load_image(A)
+  B_img, B_img_ = load_image(B)
+  Xs_ = sess.run(Xs, feed_dict={X: A_img_, Y: B_img_})
+  print("2")
+  output = deprocess(Xs_)[0]
+  output = np.array(np.array(output)*255,dtype=np.uint8)
+  # output = cv2.cvtColor(output, cv2.COLOR_RGB2BGR)
+
+  image = Image.fromarray(output)
+  inputs = ImageLoader.load_image(image)
+  preds = model_scale(inputs)
+  print(preds.shape)
+  ImageLoader.save_image(preds, 'output/scaled_2x.png')
+
+
+
+def makeupTransfer(arr1,arr2):
+  print("-"*8)
+  shutil.rmtree("input/")
+  os.makedirs("input/")
+  output1 = cv2.cvtColor(arr1, cv2.COLOR_BGR2RGB)
+  output2 = cv2.cvtColor(arr2, cv2.COLOR_BGR2RGB)
+  cv2.imwrite("input/original.png",output1)
+  cv2.imwrite("input/ref.png",output2)
+  no_makeup = "input/original.png"
+  makeup = "input/ref.png"
+  inference(no_makeup, makeup)
+  return cv2.cvtColor(cv2.imread("output/scaled_2x.png"), cv2.COLOR_BGR2RGB)
+
+app = gr.Interface(fn=makeupTransfer,
+             inputs=[gr.Image(label="Reference Image",type='numpy'),
+                     gr.Image(label="Makeup Image",type='numpy')],
+             outputs=gr.Image(label="Makeup Transfer Image",type='numpy'),
+             title="MakeUp Transfer APP")
+
+app.launch(share=True)

dmt.pb

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9d4a54b5d6fad0b2be7939630aec03506ec8912b7a1b5e8529a709ec5e022947
+size 47937309

requirements.txt

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+imageio==2.31.6
+numpy==1.25.2
+opencv_contrib_python==4.8.0.76
+opencv_python==4.8.0.76
+opencv_python_headless==4.9.0.80
+tensorflow==2.15.0
+super-image
+gradio