Create app.py

app.py

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+from huggingface_hub import from_pretrained_keras
+import gradio as gr
+from skimage.io import imsave
+from skimage.color import lab2rgb
+from tensorflow.keras.utils import img_to_array, load_img
+
+repo_id="saruizn/trabajo"
+
+model = from_pretrained_keras(repo_id)
+
+def predict(img):
+    partes=[]
+    imsave("input.jpg",img)
+    imag = img_to_array(load_img("input.jpg"))
+    partes=divideImage(imag)
+    i=0
+    imagenes=[]
+    for imgp in partes:
+        nombre="result"+str(i)+".png"
+        imsave(nombre,imgp)
+        guardarImagen(nombre,i,imagenes)
+        i=i+1
+    imagenFinal=juntaImage(imagenes)
+    return imagenFinal
+
+def guardarImagen(foto,i,imagenes):
+    color_me = []
+    img = img_to_array(load_img(foto))
+    img = resize(img ,(256,256))
+    color_me.append(img)
+    color_me = np.array(color_me, dtype=float)
+    color_me = rgb2lab(1.0/255*color_me)[:,:,:,0]
+    color_me = color_me.reshape(color_me.shape+(1,))
+    
+    output = model.predict(color_me)
+    output = output * 128 * 8
+    
+      
+    result = np.zeros((256, 256, 3))
+    result[:,:,0] = color_me[0][:,:,0]
+    result[:,:,1:] = output[0]
+    imagenes.append(lab2rgb(result))
+    imsave("result"+str(i)+".png", lab2rgb(result))
+
+def divideImage(img):
+    salida=[]
+    for i in range(0,3):
+        for j in range(0,5):
+            salida.append(img[i*256:i*256+256,j*256:j*256+256])
+        salida.append(img[i*256:i*256+256,1372-256:1372])
+    for j in range(0,5):
+        salida.append(img[929-256:929,j*256:j*256+256])
+    salida.append(img[929-256:929,1372-256:1372])
+    return salida
+
+def juntaImage(X):
+    salida=np.zeros((929, 1372, 3))
+    im=0
+    for i in range(0,3):
+        for j in range(0,5):
+            salida[i*256:i*256+256,j*256:j*256+256]=X[im]
+            im=im+1
+        salida[i*256:i*256+256,1372-256:1372]=X[im]
+        im=im+1
+    for j in range(0,5):
+        salida[929-256:929,j*256:j*256+256]=X[im]
+        im=im+1
+    salida[929-256:929,1372-256:1372]=X[im]
+    return salida
+
+
+
+
+gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(929, 1372)), outputs=gr.outputs.Image(shape=(929, 1372))).launch(share=False)