feat: add model hash support for a1111

modules/async_worker.py

@@ -14,6 +14,7 @@ async_tasks = []
 def worker():
     global async_tasks
 
+    import os
     import traceback
     import math
     import json
@@ -42,7 +43,7 @@ def worker():
     from modules.private_logger import log
     from extras.expansion import safe_str
     from modules.util import remove_empty_str, HWC3, resize_image, \
-        get_image_shape_ceil, set_image_shape_ceil, get_shape_ceil, resample_image, erode_or_dilate
+        get_image_shape_ceil, set_image_shape_ceil, get_shape_ceil, resample_image, erode_or_dilate, calculate_sha256, quote
     from modules.upscaler import perform_upscale
 
     try:
@@ -201,6 +202,17 @@ def worker():
             modules.patch.adm_scaler_end = advanced_parameters.adm_scaler_end = 0.0
             steps = 8
 
+        base_model_path = os.path.join(modules.config.path_checkpoints, base_model_name)
+        base_model_hash = calculate_sha256(base_model_path)[0:10]
+
+        lora_hashes = []
+        for (n, w) in loras:
+            if n != 'None':
+                lora_path = os.path.join(modules.config.path_loras, n)
+                lora_hashes.append(f'{n.split('.')[0]}: {calculate_sha256(lora_path)[0:10]}')
+        lora_hashes_string = ", ".join(lora_hashes)
+        print(lora_hashes_string)
+
         modules.patch.adaptive_cfg = advanced_parameters.adaptive_cfg
         print(f'[Parameters] Adaptive CFG = {modules.patch.adaptive_cfg}')
 
@@ -854,16 +866,17 @@ def worker():
                         "CFG scale": cfg_scale,
                         "Seed": task['task_seed'],
                         "Size": f"{width}x{height}",
-                        #"Model hash": p.sd_model_hash if opts.add_model_hash_to_info else None,
-                        "Model": base_model_name,
+                        "Model hash": base_model_hash,
+                        "Model": base_model_name.split('.')[0],
+                        "Lora hashes": lora_hashes_string,
                         "Denoising strength": denoising_strength,
                         "Version": f'Fooocus v{fooocus_version.version}',
-                        "User": 'mashb1t',
+                        "User": 'mashb1t'
                     }
 
-                    generation_params_text = ", ".join([k if k == v else f'{k}: {v}' for k, v in generation_params.items() if v is not None])
+                    generation_params_text = ", ".join([k if k == v else f'{k}: {quote(v)}' for k, v in generation_params.items() if v is not None])
                     negative_prompt_text = f"\nNegative prompt: {raw_negative_prompt}" if raw_negative_prompt else ""
-                    metadata_string = f"{raw_prompt}{raw_negative_prompt}\n{generation_params_text}".strip()
+                    metadata_string = f"{raw_prompt}{negative_prompt_text}\n{generation_params_text}".strip()
 
                 for x in imgs:
                     d = [

modules/util.py

@@ -4,8 +4,10 @@ import random
 import math
 import os
 import cv2
+import json
 
 from PIL import Image
+from hashlib import sha256
 
 
 LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.LANCZOS)
@@ -175,3 +177,19 @@ def get_files_from_folder(folder_path, exensions=None, name_filter=None):
                 filenames.append(path)
 
     return sorted(filenames, key=lambda x: -1 if os.sep in x else 1)
+
+def calculate_sha256(filename):
+    hash_sha256 = sha256()
+    blksize = 1024 * 1024
+
+    with open(filename, "rb") as f:
+        for chunk in iter(lambda: f.read(blksize), b""):
+            hash_sha256.update(chunk)
+
+    return hash_sha256.hexdigest()
+
+def quote(text):
+    if ',' not in str(text) and '\n' not in str(text) and ':' not in str(text):
+        return text
+
+    return json.dumps(text, ensure_ascii=False)