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import random
import gradio as gr
import huggingface_hub
import imageio
import numpy as np
import onnxruntime as rt
from numpy.random import RandomState
from skimage import transform
class Model:
def __init__(self):
self.g_synthesis = None
self.g_mapping = None
self.load_models()
def load_models(self):
providers = ['CUDAExecutionProvider', 'CPUExecutionProvider']
g_mapping_path = huggingface_hub.hf_hub_download("skytnt/waifu-gan", "g_mapping.onnx")
g_synthesis_path = huggingface_hub.hf_hub_download("skytnt/waifu-gan", "g_synthesis.onnx")
self.g_mapping = rt.InferenceSession(g_mapping_path, providers=providers)
self.g_synthesis = rt.InferenceSession(g_synthesis_path, providers=providers)
def get_img(self, w):
img = self.g_synthesis.run(None, {'w': w})[0]
return (img.transpose(0, 2, 3, 1) * 127.5 + 128).clip(0, 255).astype(np.uint8)[0]
def get_w(self, z, psi1, psi2):
return self.g_mapping.run(None, {'z': z, 'psi': np.asarray([psi1, psi2], dtype=np.float32)})[0]
def gen_video(self, w1, w2, path, frame_num=10):
video = imageio.get_writer(path, mode='I', fps=frame_num // 2, codec='libx264', bitrate='16M')
lin = np.linspace(0, 1, frame_num)
for i in range(0, frame_num):
img = self.get_img(((1 - lin[i]) * w1) + (lin[i] * w2))
video.append_data(img)
video.close()
def get_thumbnail(img):
img_new = np.full((192, 288, 3), 200, dtype=np.uint8)
img_new[:, 80:208] = transform.resize(img, (192, 128), preserve_range=True)
return img_new
def gen_fn(method, seed, psi1, psi2):
if method == 0:
seed = random.randint(0, 2 ** 32 -1)
z = RandomState(int(seed)).randn(1, 1024)
w = model.get_w(z.astype(dtype=np.float32), psi1, psi2)
img_out = model.get_img(w)
return img_out, seed, w, get_thumbnail(img_out)
def gen_video_fn(w1, w2, frame):
if w1 is None or w2 is None:
return None
model.gen_video(w1, w2, "video.mp4", int(frame))
return "video.mp4"
if __name__ == '__main__':
model = Model()
app = gr.Blocks()
with app:
gr.Markdown("# Waifu GAN\n\n"
"![visitor badge](https://visitor-badge.glitch.me/badge?page_id=skytnt.waifu-gan)\n\n")
with gr.Tabs():
with gr.TabItem("generate image"):
with gr.Row():
with gr.Column():
with gr.Row():
gen_input1 = gr.Radio(label="method", value="random",
choices=["random", "use seed"], type="index")
gen_input2 = gr.Slider(minimum=0, maximum=2 ** 32 - 1, step=1, value=0,
label="seed")
gen_input3 = gr.Slider(minimum=0, maximum=1, step=0.01, value=1, label="truncation psi 1")
gen_input4 = gr.Slider(minimum=0, maximum=1, step=0.01, value=1, label="truncation psi 2")
with gr.Group():
gen_submit = gr.Button("Generate", variant="primary")
with gr.Column():
gen_output1 = gr.Image(label="output image")
select_img_input_w1 = gr.Variable()
select_img_input_img1 = gr.Variable()
with gr.TabItem("generate video"):
with gr.Row():
with gr.Column():
gr.Markdown("## generate video between 2 images")
with gr.Row():
with gr.Column():
gr.Markdown("please select image 1")
select_img1_dropdown = gr.Radio(label="source", value="current generated image",
choices=["current generated image"], type="index")
with gr.Group():
select_img1_button = gr.Button("Select", variant="primary")
select_img1_output_img = gr.Image(label="selected image 1")
select_img1_output_w = gr.Variable()
with gr.Column():
gr.Markdown("please select image 2")
select_img2_dropdown = gr.Radio(label="source", value="current generated image",
choices=["current generated image"], type="index")
with gr.Group():
select_img2_button = gr.Button("Select", variant="primary")
select_img2_output_img = gr.Image(label="selected image 2")
select_img2_output_w = gr.Variable()
generate_video_frame = gr.Slider(minimum=10, maximum=30, step=1, label="frame", value=15)
with gr.Group():
generate_video_button = gr.Button("Generate", variant="primary")
with gr.Column():
generate_video_output = gr.Video(label="output video")
gen_submit.click(gen_fn, [gen_input1, gen_input2, gen_input3, gen_input4],
[gen_output1, gen_input2, select_img_input_w1, select_img_input_img1])
select_img1_button.click(lambda i, img1, w1: (img1, w1),
[select_img1_dropdown, select_img_input_img1, select_img_input_w1],
[select_img1_output_img, select_img1_output_w])
select_img2_button.click(lambda i, img1, w1: (img1, w1),
[select_img2_dropdown, select_img_input_img1, select_img_input_w1],
[select_img2_output_img, select_img2_output_w])
generate_video_button.click(gen_video_fn,
[select_img1_output_w, select_img2_output_w, generate_video_frame],
[generate_video_output])
app.launch()
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