60 lines
1.9 KiB
Python
60 lines
1.9 KiB
Python
import math
|
|
import os
|
|
import sys
|
|
import traceback
|
|
|
|
import modules.scripts as scripts
|
|
import gradio as gr
|
|
|
|
from modules.processing import Processed, process_images
|
|
from PIL import Image
|
|
from modules.shared import opts, cmd_opts, state
|
|
|
|
|
|
class Script(scripts.Script):
|
|
def title(self):
|
|
return "Batch processing"
|
|
|
|
def show(self, is_img2img):
|
|
return is_img2img
|
|
|
|
def ui(self, is_img2img):
|
|
input_dir = gr.Textbox(label="Input directory", lines=1)
|
|
output_dir = gr.Textbox(label="Output directory", lines=1)
|
|
|
|
return [input_dir, output_dir]
|
|
|
|
def run(self, p, input_dir, output_dir):
|
|
images = [file for file in [os.path.join(input_dir, x) for x in os.listdir(input_dir)] if os.path.isfile(file)]
|
|
|
|
batch_count = math.ceil(len(images) / p.batch_size)
|
|
print(f"Will process {len(images)} images in {batch_count} batches.")
|
|
|
|
p.batch_count = 1
|
|
p.do_not_save_grid = True
|
|
p.do_not_save_samples = True
|
|
|
|
state.job_count = batch_count
|
|
|
|
for batch_no in range(batch_count):
|
|
batch_images = []
|
|
for path in images[batch_no*p.batch_size:(batch_no+1)*p.batch_size]:
|
|
try:
|
|
img = Image.open(path)
|
|
batch_images.append((img, path))
|
|
except:
|
|
print(f"Error processing {path}:", file=sys.stderr)
|
|
print(traceback.format_exc(), file=sys.stderr)
|
|
|
|
if len(batch_images) == 0:
|
|
continue
|
|
|
|
state.job = f"{batch_no} out of {batch_count}: {batch_images[0][1]}"
|
|
p.init_images = [x[0] for x in batch_images]
|
|
proc = process_images(p)
|
|
for image, (_, path) in zip(proc.images, batch_images):
|
|
filename = os.path.basename(path)
|
|
image.save(os.path.join(output_dir, filename))
|
|
|
|
return Processed(p, [], p.seed, "")
|