move save params to after generate

html/reference.json

@@ -23,11 +23,6 @@
     "path": "segmind/tiny-sd",
     "desc": "Segmind's Tiny-SD offers a compact, efficient, and distilled version of Realistic Vision 4.0 and is up to 80% faster than SD1.5",
     "preview": "segmind--tiny-sd.jpg"
-  },
-    "LCM SD-XL": {
-    "path": "latent-consistency/lcm-sdxl",
-    "desc": "Latent Consistencey Models enable swift inference with minimal steps on any pre-trained LDMs, including Stable Diffusion. By distilling classifier-free guidance into the model's input, LCM can generate high-quality images in very short inference time. LCM can generate quality images in as few as 3-4 steps, making it blazingly fast.",
-    "preview": "latent-consistency--lcm-sdxl.jpg"
   },
   "LCM SD-1.5 Dreamshaper 7": {
     "path": "SimianLuo/LCM_Dreamshaper_v7",

modules/images.py

@@ -541,6 +541,8 @@ def atomically_save_image():
             entry = { 'id': idx, 'filename': filename, 'time': datetime.datetime.now().isoformat(), 'info': exifinfo }
             entries.append(entry)
             shared.writefile(entries, fn, mode='w')
+        with open(os.path.join(paths.data_path, "params.txt"), "w", encoding="utf8") as file:
+            file.write(exifinfo)
         save_queue.task_done()
 
 

modules/processing.py

@@ -851,10 +851,6 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
                     modules.extra_networks.activate(p, extra_network_data)
             if p.scripts is not None and isinstance(p.scripts, modules.scripts.ScriptRunner):
                 p.scripts.process_batch(p, batch_number=n, prompts=p.prompts, seeds=p.seeds, subseeds=p.subseeds)
-            if n == 0:
-                with open(os.path.join(modules.paths.data_path, "params.txt"), "w", encoding="utf8") as file:
-                    processed = Processed(p, [], p.seed, "")
-                    file.write(processed.infotext(p, 0))
             step_multiplier = 1
             sampler_config = modules.sd_samplers.find_sampler_config(p.sampler_name)
             step_multiplier = 2 if sampler_config and sampler_config.options.get("second_order", False) else 1

modules/ui_tempdir.py

@@ -4,7 +4,7 @@ from collections import namedtuple
 from pathlib import Path
 import gradio as gr
 from PIL import Image, PngImagePlugin
-from modules import shared, errors
+from modules import shared, errors, paths
 
 
 Savedfile = namedtuple("Savedfile", ["name"])
@@ -69,6 +69,10 @@ def pil_to_temp_file(self, img: Image, dir: str, format="png") -> str: # pylint:
         name = tmp.name
         img.save(name, pnginfo=(metadata if use_metadata else None))
         shared.log.debug(f'Saving temp: image="{name}"')
+    params = ', '.join([f'{k}: {v}' for k, v in img.info.items()])
+    params = params[12:] if params.startswith('parameters: ') else params
+    with open(os.path.join(paths.data_path, "params.txt"), "w", encoding="utf8") as file:
+        file.write(params)
     return name