move to gradio

app.py

@@ -1,12 +1,64 @@
-import os, glob, sys
-import pickle
-import streamlit as st
+
+import sys, os
+import gradio as gr
+import numpy as np
+sys.path.append('stylegan3')
 import utils
 
+def to_uint8(im, ndim=2):
+    im -= np.min(im)
+    im /= np.max(im)
+    im *= 255.
+    im = np.asarray(im, dtype=np.uint8)
+    if ndim == 3:    
+        if im.ndim == 2:
+            im = np.expand_dims(im, axis=-1)
+        elif im.ndim == 3:
+            if im.shape[0] == 1: 
+                np.transpose(im, (1,2,0))
+        im = np.tile(im, (1,1,3)) #make fake RGB
+        return im
+    elif ndim ==2:
+        if im.ndim == 2:
+            return im
+        if im.ndim == 3:
+            if im.shape[0] == 1:  #[1, H, W]
+                return im[0,...]
+            elif im.shape[2] == 1: #[H, W, 1]
+                return im[...,0]
+            else:
+                raise AssertionError(f"Unexpected image passed to to_uint8 with shape: {np.shape(im)}.")
+
+
 in_gpu = False
 num_images = 1
 G = utils.load_default_gen(in_gpu=in_gpu)
 sampler = utils.SampleFromGAN(G=G, z_shp=[num_images, G.z_dim], in_gpu=in_gpu)
-button_on_click = utils.Plot(im_gen=sampler)
-button_gen_clicked = st.button(label='Generate an image', key='n', on_click=button_on_click)
 
+def sample_GAN():
+    im = sampler()
+    im = im.numpy()
+    im = np.transpose(im, (1,2,0))
+    im = np.squeeze(im) #if single channel (yes), drop it.
+    # print(f"sample_linearBP: im shape: {im.shape}; min: {np.min(im)}, max: {np.max(im)}.")
+    im = to_uint8(im, ndim=2)
+    # print(f'1. uint image shape: {im.shape}')
+    return im
+
+
+title="Generate fake linear array images"
+description="Generate fake linear array images."
+
+with gr.Blocks() as demo:
+    gr.Markdown(description)
+    # with gr.Row(equal_height=True):
+    #     button_gen = gr.Button("Generate fake linear image")
+    # with gr.Row(equal_height=True):
+    #     output_im = gr.Image(type="numpy", shape=(256, 256), image_mode="L", label="fake image", interactive=False) #grayscale image
+    with gr.Column(scale=1):
+        button_gen = gr.Button("Generate fake linear image")
+    with gr.Column(scale=2):
+        output_im = gr.Image(type="numpy", shape=(256, 256), image_mode="L", label="fake image", interactive=False) #grayscale image
+    button_gen.click(sample_GAN, inputs=None, outputs=output_im)
+    
+demo.launch(share=False, show_tips=True, enable_queue=True)

app_streamlit.py

@@ -0,0 +1,12 @@
+import os, glob, sys
+import pickle
+import streamlit as st
+import utils
+
+in_gpu = False
+num_images = 1
+G = utils.load_default_gen(in_gpu=in_gpu)
+sampler = utils.SampleFromGAN(G=G, z_shp=[num_images, G.z_dim], in_gpu=in_gpu)
+button_on_click = utils.Plot(im_gen=sampler)
+button_gen_clicked = st.button(label='Generate an image', key='n', on_click=button_on_click)
+