🎶 Octaves set automatically from target size, or by command.

Author: alexjc

src/texturize/__main__.py

@@ -30,7 +30,8 @@
     --variations=V          Number of images to generate at same time. [default: 1]
     --seed=SEED             Configure the random number generation.
     --mode=MODE             Either "patch" or "gram" to manually specify critics.
-    --octaves=O             Number of octaves to process. [default: 5]
+    --octaves=O             Number of octaves to process. Defaults to 5 for 512x512, or
+                            4 for 256x256 equivalent pixel count.
     --threshold=T           Quality for optimization, lower is better.  Defaults to 1e-3
                             for "patch" and 1e-7 for "gram".
     --iterations=I          Maximum number of iterations each octave. [default: 99]
@@ -51,7 +52,6 @@
 
 import os
 import glob
-import math
 import itertools
 
 import docopt
@@ -83,7 +83,7 @@ def split_string(text: str):
             "variations": Use(int),
             "seed": Or(None, Use(int)),
             "mode": Or(None, "patch", "gram", "hist"),
-            "octaves": Use(int),
+            "octaves": Or(None, Use(int)),
             "threshold": Or(None, Use(float)),
             "iterations": Use(int),
             "device": Or(None, "cpu", "cuda"),
@@ -134,7 +134,7 @@ def main():
         if command == "enhance":
             zoom = config["zoom"]
             cmd = commands.Enhance(target_img, source_img, mode=mode, zoom=zoom)
-            config["octaves"] = int(math.log(zoom, 2) + 1.0)
+            config["octaves"] = cmd.octaves
             config["size"] = (target_img.size[0] * zoom, target_img.size[1] * zoom)
         if command == "remake":
             cmd = commands.Remake(

src/texturize/api.py

@@ -1,6 +1,7 @@
 # neural-texturize — Copyright (c) 2020, Novelty Factory KG.  See LICENSE for details.
 
 import os
+import math
 
 import torch
 import torch.nn.functional as F
@@ -16,7 +17,7 @@ def process_iterations(
     cmd,
     log: object = None,
     size: tuple = None,
-    octaves: int = -1,
+    octaves: int = None,
     variations: int = 1,
     iterations: int = 200,
     threshold: float = 1e-5,
@@ -26,9 +27,13 @@ def process_iterations(
     """Synthesize a new texture and return a PyTorch tensor at each iteration.
     """
 
+    # Configure the default options dynamically, unless overriden.
+    threshold = threshold or {"patch": 1e-3, "gram": 1e-7, "hist": 1e-6}[cmd.mode]
+    factor = math.sqrt((size[0] * size[1]) / (32 ** 2))
+    octaves = octaves or getattr(cmd, "octaves", int(math.log(factor, 2) + 1.0))
+
     # Setup the application to use throughout the synthesis.
     app = Application(log, device, precision)
-    threshold = threshold or {"patch": 1e-3, "gram": 1e-7, "hist": 1e-6}[cmd.mode]
 
     # Encoder used by all the critics at every octave.
     encoder = models.VGG11(pretrained=True, pool_type=torch.nn.AvgPool2d)

src/texturize/commands.py

@@ -1,5 +1,7 @@
 # neural-texturize — Copyright (c) 2020, Novelty Factory KG.  See LICENSE for details.
 
+import math
+
 import torch
 import torch.nn.functional as F
 
@@ -89,8 +91,9 @@ def prepare_seed_tensor(self, app, size, previous=None):
 
 
 class Enhance(Command):
-    def __init__(self, target, source, mode=None):
+    def __init__(self, target, source, mode=None, zoom=1):
         self.mode = mode or "gram"
+        self.octaves = int(math.log(zoom, 2) + 1.0)
         self.critics = list(create_default_critics(self.mode).values())
         self.source = load_tensor_from_image(source, device="cpu")
         self.target = load_tensor_from_image(target, device="cpu")