OmniSVG-3B / tokenizer.py
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Update tokenizer.py
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import numpy as np
import torch
import yaml
from typing import List, Tuple, Dict, Optional, Union
from deepsvg.difflib.tensor import SVGTensor
from deepsvg.svglib.svg import SVG
from deepsvg.svglib.geom import Bbox
class SVGTokenizer:
"""SVG tokenizer for converting between tokens and SVG representations"""
def __init__(self, config_path: str = "config.yaml"):
with open(config_path, 'r') as f:
self.config = yaml.safe_load(f)
# Extract configuration values
self.tokens_config = self.config['tokens']
self.coordinates_config = self.config['coordinates']
self.colors_config = self.config['colors']
self.svg_commands = self.config['svg_commands']
self.pixel2xy = self._create_pixel2xy_mapping()
def _create_pixel2xy_mapping(self) -> Dict[int, np.ndarray]:
"""Create mapping from pixel indices to xy coordinates"""
bbox = self.coordinates_config['bbox']
coord_pad = self.coordinates_config['coord_pad_offset']
svg_end = self.tokens_config['svg_end']
pixel2xy = {}
x = np.linspace(0, bbox-1, bbox)
y = np.linspace(0, bbox-1, bbox)
xx, yy = np.meshgrid(x, y)
xy_grid = (np.array((xx.ravel(), yy.ravel())).T).astype(int)
for pixel, xy in enumerate(xy_grid):
pixel2xy[pixel] = xy + coord_pad + svg_end
return pixel2xy
def token_to_color(self, color_token: int) -> str:
try:
color_token_start = self.colors_config['color_token_start']
max_color_tokens = self.colors_config['max_color_tokens']
# Check special color tokens
if color_token == color_token_start:
return "none" # No color
elif color_token == color_token_start + 1:
return "currentColor" # Special color
color_index = color_token - (color_token_start + 2)
if color_index < 0 or color_index >= max_color_tokens:
print(f"Warning: Color token {color_token} out of range, using default color")
return "#808080" # Gray as default
r = (color_index >> 8) & 0xF
g = (color_index >> 4) & 0xF
b = color_index & 0xF
r = (r << 4) | r
g = (g << 4) | g
b = (b << 4) | b
return f"#{r:02x}{g:02x}{b:02x}"
except Exception as e:
print(f"Error in token_to_color: {e}")
return "#808080"
def pixel_to_xy(self, pixel: int) -> np.ndarray:
"""Convert pixel token to xy coordinates"""
base_offset = self.tokens_config['base_offset']
pix_pad = self.coordinates_config['pix_pad_offset']
svg_end = self.tokens_config['svg_end']
if self.tokens_config['eom'] < pixel < pix_pad + svg_end:
xy = np.array([pixel - base_offset, pixel - base_offset]).astype(int)
return xy
elif pix_pad + svg_end <= pixel < self.colors_config['cmd_fill'] + base_offset + svg_end:
pixel_index = pixel - pix_pad - svg_end
if pixel_index in self.pixel2xy:
return self.pixel2xy[pixel_index] - base_offset
else:
raise ValueError(f"Invalid pixel index: {pixel_index}")
else:
raise ValueError(f"Invalid pixel token: {pixel}")
def raster_svg(self, pixels: np.ndarray) -> List[List[torch.Tensor]]:
"""Convert pixel sequence to SVG tensor representation"""
try:
adjustment = self.tokens_config['num_end_token'] + self.tokens_config['svg_end'] + 2 # 8
pixels = pixels - adjustment
svg_tensors = []
path_tensor = []
i = 0
while i < len(pixels):
try:
pix = pixels[i]
if pix[0] == self.svg_commands['move']: # Move command
cmd_tensor = np.zeros(14)
cmd_tensor[0] = 0
if i + 2 >= len(pixels):
break
cmd_tensor[12:14] = pixels[i+2]
start_pos = pixels[i+1]
end_pos = pixels[i+2]
if np.all(start_pos == end_pos) and path_tensor:
svg_tensors.append(torch.tensor(path_tensor))
path_tensor = []
path_tensor.append(cmd_tensor.tolist())
i += 3
elif pix[0] == self.svg_commands['line']: # Line command
cmd_tensor = np.zeros(14)
cmd_tensor[0] = 1
if i + 1 >= len(pixels):
break
cmd_tensor[12:14] = pixels[i+1]
path_tensor.append(cmd_tensor.tolist())
i += 2
elif pix[0] == self.svg_commands['curve']: # Curve command
cmd_tensor = np.zeros(14)
cmd_tensor[0] = 2
if i + 3 >= len(pixels):
break
cmd_tensor[8:10] = pixels[i+1]
cmd_tensor[10:12] = pixels[i+2]
cmd_tensor[12:14] = pixels[i+3]
path_tensor.append(cmd_tensor.tolist())
i += 4
elif pix[0] == self.svg_commands['arc']: # Arc command
cmd_tensor = np.zeros(14)
cmd_tensor[0] = 3
if i + 5 >= len(pixels):
break
radius = pixels[i+1]
x_axis_rot = pixels[i+2][0]
large_arc_flg = pixels[i+3][0]
sweep_flg = pixels[i+4][0]
end_pos = pixels[i+5]
cmd_tensor[1:3] = radius
cmd_tensor[3] = x_axis_rot
cmd_tensor[4] = large_arc_flg
cmd_tensor[5] = sweep_flg
cmd_tensor[12:14] = end_pos
path_tensor.append(cmd_tensor.tolist())
i += 6
elif pix[0] == self.svg_commands['close']: # Close command
cmd_tensor = np.zeros(14)
cmd_tensor[0] = 6
if i + 1 >= len(pixels):
break
cmd_tensor[12:14] = pixels[i+1]
path_tensor.append(cmd_tensor.tolist())
i += 2
else:
i += 1
except IndexError:
print(f"Index error at position {i}, stopping SVG processing")
break
if path_tensor:
svg_tensors.append(torch.tensor(path_tensor))
return [svg_tensors]
except Exception as e:
print(f"Error in raster_svg: {e}")
return []
def extract_colors_from_tokens(self, tokens: List[int]) -> List[int]:
colors = []
base_offset = self.tokens_config['base_offset']
color_start = self.colors_config['color_start_offset']
color_end = self.colors_config['color_end_offset']
for token in tokens:
if color_start <= token < color_end:
colors.append(token - 1 - base_offset)
return colors
def process_generated_tokens(self, output_ids: torch.Tensor) -> Tuple[np.ndarray, List[int]]:
# Remove <bos> and <eos> tokens
generated_pixels = output_ids[:, 1:-1].tolist()
generated_xy = []
generated_colors = []
for pixel_sequence in generated_pixels:
xy_sequence = []
colors = []
for pixel in pixel_sequence:
try:
if self.tokens_config['eom'] < pixel < self.coordinates_config['pix_pad_offset'] + self.tokens_config['svg_end']:
xy = self.pixel_to_xy(pixel)
xy_sequence.append(xy)
elif self.coordinates_config['pix_pad_offset'] + self.tokens_config['svg_end'] <= pixel < self.colors_config['cmd_fill'] + self.tokens_config['base_offset'] + self.tokens_config['svg_end']:
xy = self.pixel_to_xy(pixel)
xy_sequence.append(xy)
elif self.colors_config['color_start_offset'] <= pixel < self.colors_config['color_end_offset']:
colors.append(pixel - 1 - self.tokens_config['base_offset'])
except ValueError as e:
print(f"Error processing pixel {pixel}: {e}")
continue
if xy_sequence:
generated_xy = np.vstack(xy_sequence)
generated_colors = colors
return generated_xy, generated_colors
def apply_colors_to_svg(self, svg_tensors: Union[List[torch.Tensor], List[List[torch.Tensor]]], colors: Optional[List[int]]) -> SVG:
paths = []
bbox = self.coordinates_config['bbox']
flat_tensors = []
if svg_tensors and isinstance(svg_tensors[0], list):
for tensor_list in svg_tensors:
flat_tensors.extend(tensor_list)
else:
flat_tensors = svg_tensors
if not flat_tensors:
raise ValueError("No valid SVG tensors provided")
if colors is None:
colors = []
for i, path_tensor in enumerate(flat_tensors):
try:
path = SVGTensor.from_data(path_tensor)
path = SVG.from_tensor(path.data, viewbox=Bbox(bbox))
if i < len(colors):
color_token = colors[i]
actual_color = self.token_to_color(color_token)
else:
actual_color = "none"
for path_group in path:
path_group.color = actual_color
path_group.stroke_color = "none"
path.fill_(True)
paths.append(path)
except Exception as e:
print(f"Error processing path {i}: {e}")
continue
if not paths:
raise ValueError("No valid paths could be generated")
path_groups = paths[0].svg_path_groups
for i in range(1, len(paths)):
if i < len(paths):
path_groups.extend(paths[i].svg_path_groups)
svg = SVG(path_groups, viewbox=Bbox(bbox))
return svg