Delete app.py

app.py

@@ -1,74 +0,0 @@
-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)