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SnapOtter/packages/ai/python/upscale.py
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"""Image upscaling with Real-ESRGAN fallback to Lanczos."""
import sys
import json
import os
def emit_progress(percent, stage):
"""Emit structured progress to stderr for bridge.ts to capture."""
print(json.dumps({"progress": percent, "stage": stage}), file=sys.stderr, flush=True)
REALESRGAN_MODEL_PATH = os.environ.get(
"REALESRGAN_MODEL_PATH",
"/opt/models/realesrgan/RealESRGAN_x4plus.pth",
)
def main():
input_path = sys.argv[1]
output_path = sys.argv[2]
settings = json.loads(sys.argv[3]) if len(sys.argv) > 3 else {}
scale = settings.get("scale", 2)
try:
emit_progress(10, "Loading upscale model")
from PIL import Image
img = Image.open(input_path)
new_size = (img.width * scale, img.height * scale)
# Try Real-ESRGAN first
try:
# Redirect stdout to stderr so basicsr/realesrgan init messages
# cannot contaminate our JSON result on stdout.
stdout_fd = os.dup(1)
os.dup2(2, 1)
try:
from basicsr.archs.rrdbnet_arch import RRDBNet
from realesrgan import RealESRGANer
from gpu import gpu_available
import numpy as np
import torch
finally:
# Restore stdout after imports
os.dup2(stdout_fd, 1)
os.close(stdout_fd)
if not os.path.exists(REALESRGAN_MODEL_PATH):
raise FileNotFoundError(f"RealESRGAN model not found: {REALESRGAN_MODEL_PATH}")
use_gpu = gpu_available()
device = torch.device("cuda" if use_gpu else "cpu")
# RealESRGAN_x4plus is a 4x model internally
model = RRDBNet(
num_in_ch=3,
num_out_ch=3,
num_feat=64,
num_block=23,
num_grow_ch=32,
scale=4,
)
upsampler = RealESRGANer(
scale=4,
model_path=REALESRGAN_MODEL_PATH,
model=model,
half=use_gpu,
device=device,
)
emit_progress(20, "Model ready")
img_array = np.array(img.convert("RGB"))
emit_progress(25, "Upscaling image")
output, _ = upsampler.enhance(img_array, outscale=scale)
emit_progress(90, "Upscaling complete")
result = Image.fromarray(output)
emit_progress(95, "Saving result")
result.save(output_path)
method = "realesrgan"
except (ImportError, FileNotFoundError, RuntimeError, OSError):
# RealESRGAN unavailable or failed - fall back to Lanczos
emit_progress(50, "Upscaling with Lanczos")
img_upscaled = img.resize(new_size, Image.LANCZOS)
emit_progress(95, "Saving result")
img_upscaled.save(output_path)
method = "lanczos"
print(
json.dumps(
{
"success": True,
"scale": scale,
"width": new_size[0],
"height": new_size[1],
"method": method,
}
)
)
except ImportError:
print(
json.dumps(
{
"success": False,
"error": "Pillow is not installed. Install with: pip install Pillow",
}
)
)
sys.exit(1)
except Exception as e:
print(json.dumps({"success": False, "error": str(e)}))
sys.exit(1)
if __name__ == "__main__":
main()