asdasd

app.py

@@ -6,11 +6,11 @@ import torchvision
 from networks_fastgan import MyGenerator
 import click
 import PIL
-
-
+from image_generator import generate_images
 
 def image_generation(model, number_of_images=1):
     G = MyGenerator.from_pretrained("Cropinky/projected_gan_impressionism")
+    generate_images(seeds = 10-15, outdir="out")
     return f"generating {number_of_images} images from {model}"
 if __name__ == "__main__":
 

image_generator.py

@@ -11,13 +11,11 @@
 import os
 import re
 from typing import List, Optional, Tuple, Union
-
 import click
-import dnnlib
 import numpy as np
 import PIL.Image
 import torch
-import legacy
+from networks_fastgan import MyGenerator
 
 #----------------------------------------------------------------------------
 
@@ -68,7 +66,7 @@ def make_transform(translate: Tuple[float,float], angle: float):
 #----------------------------------------------------------------------------
 
 @click.command()
-@click.option('--network', 'network_pkl', help='Network pickle filename', required=True)
+@click.option('--network', 'network_pkl', help='Network pickle filename', required=False)
 @click.option('--seeds', type=parse_range, help='List of random seeds (e.g., \'0,1,4-6\')', required=True)
 @click.option('--trunc', 'truncation_psi', type=float, help='Truncation psi', default=1, show_default=True)
 @click.option('--class', 'class_idx', type=int, help='Class label (unconditional if not specified)')
@@ -77,7 +75,6 @@ def make_transform(translate: Tuple[float,float], angle: float):
 @click.option('--rotate', help='Rotation angle in degrees', type=float, default=0, show_default=True, metavar='ANGLE')
 @click.option('--outdir', help='Where to save the output images', type=str, required=True, metavar='DIR')
 def generate_images(
-    network_pkl: str,
     seeds: List[int],
     truncation_psi: float,
     noise_mode: str,
@@ -103,10 +100,8 @@ def generate_images(
 
     print('Loading networks from "%s"...' % network_pkl)
     device = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')
-    with dnnlib.util.open_url(network_pkl) as f:
-        G = legacy.load_network_pkl(f)['G_ema'].to(device) # type: ignore
-
-    os.makedirs(outdhf_ShHdFYTLiCYbxIuldloQmxMXgPvuEyUPAkir, exist_ok=True)
+    G = MyGenerator.from_pretrained("Cropinky/projected_gan_impressionism")
+    os.makedirs(outdir, exist_ok=True)
 
     # Labels.
     label = torch.zeros([1, G.c_dim], device=device)