stablediffusion / Stable_diffusion_augmentation /plot_generated_pairs_by_class.py
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#!/usr/bin/env python3
"""Plot synthetic paired augmentation images grouped by class and modality."""
from __future__ import annotations
import argparse
import csv
import math
from collections import defaultdict
from pathlib import Path
from PIL import Image, ImageDraw, ImageFile, ImageFont, ImageOps
ImageFile.LOAD_TRUNCATED_IMAGES = True
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser(description="Create a class/modality contact sheet from paired augmentation manifest.")
parser.add_argument(
"--manifest",
type=Path,
default=Path("Stable_diffusion_augmentation/out_minority_pairs/paired_augmentation_manifest.csv"),
)
parser.add_argument(
"--output-file",
type=Path,
default=Path("Stable_diffusion_augmentation/out_minority_pairs/generated_pairs_by_class.png"),
)
parser.add_argument("--max-pairs-per-class", type=int, default=None)
parser.add_argument("--thumb-size", type=int, default=180)
parser.add_argument("--padding", type=int, default=12)
parser.add_argument("--background", default="white")
return parser.parse_args()
def load_font(size: int) -> ImageFont.ImageFont:
try:
return ImageFont.truetype("DejaVuSans.ttf", size)
except OSError:
return ImageFont.load_default()
def read_manifest(path: Path, max_pairs_per_class: int | None) -> list[dict[str, str]]:
grouped: dict[str, list[dict[str, str]]] = defaultdict(list)
with path.open(newline="") as f:
for row in csv.DictReader(f):
grouped[row["class_name"]].append(row)
rows = []
for class_name in sorted(grouped):
class_rows = grouped[class_name]
if max_pairs_per_class is not None:
class_rows = class_rows[:max_pairs_per_class]
rows.extend(class_rows)
if not rows:
raise ValueError(f"No rows found in manifest: {path}")
return rows
def truncate(text: str, max_chars: int) -> str:
if len(text) <= max_chars:
return text
return text[: max_chars - 3] + "..."
def make_sheet(rows: list[dict[str, str]], thumb_size: int, padding: int, background: str) -> Image.Image:
classes = sorted({row["class_name"] for row in rows})
grouped = {class_name: [row for row in rows if row["class_name"] == class_name] for class_name in classes}
max_pairs = max(len(items) for items in grouped.values())
columns = len(classes) * 2
header_height = 34
label_height = 26
cell_width = thumb_size
cell_height = header_height + thumb_size + label_height
width = columns * cell_width + (columns + 1) * padding
height = max_pairs * cell_height + (max_pairs + 1) * padding
sheet = Image.new("RGB", (width, height), background)
draw = ImageDraw.Draw(sheet)
header_font = load_font(14)
label_font = load_font(11)
for class_idx, class_name in enumerate(classes):
for row_idx, row in enumerate(grouped[class_name]):
for modality_idx, (modality, path_key) in enumerate(
(("clinical", "clinical_generated_path"), ("derm", "dermoscopic_generated_path"))
):
col = class_idx * 2 + modality_idx
x = padding + col * (cell_width + padding)
y = padding + row_idx * (cell_height + padding)
header = f"{class_name} {modality}"
draw.text((x, y), header, fill="black", font=header_font)
image_y = y + header_height
with Image.open(row[path_key]) as img:
thumb = ImageOps.fit(img.convert("RGB"), (thumb_size, thumb_size), method=Image.Resampling.LANCZOS)
sheet.paste(thumb, (x, image_y))
label = truncate(row["synthetic_lesion_id"], 24)
draw.text((x, image_y + thumb_size + 4), label, fill="black", font=label_font)
return sheet
def main() -> None:
args = parse_args()
manifest = args.manifest.expanduser().resolve()
if not manifest.exists():
raise FileNotFoundError(f"Manifest not found: {manifest}")
if args.thumb_size < 32:
raise ValueError("--thumb-size must be >= 32")
if args.padding < 0:
raise ValueError("--padding must be >= 0")
rows = read_manifest(manifest, args.max_pairs_per_class)
output_file = args.output_file.expanduser().resolve()
output_file.parent.mkdir(parents=True, exist_ok=True)
sheet = make_sheet(rows, args.thumb_size, args.padding, args.background)
sheet.save(output_file)
print(f"Plotted {len(rows)} synthetic pairs")
print(f"Saved contact sheet: {output_file}")
if __name__ == "__main__":
main()