Code for V2 added, completely new UI and lots of features

Author: divamgupta

README.md

@@ -1,6 +1,8 @@
 # Diffusion Bee - Stable Diffusion GUI App for MacOS
 [![Twitter](https://img.shields.io/twitter/url.svg?label=Follow%20%40divamgupta&style=social&url=https%3A%2F%2Ftwitter.com%2Fdivamgupta)](https://twitter.com/divamgupta)
 
+a
+
 
 ### Diffusion Bee is the easiest way to run Stable Diffusion locally on your Intel / M1 Mac. Comes with a one-click installer. No dependencies or technical knowledge needed.
 
@@ -14,6 +16,7 @@
 Download at https://diffusionbee.com/
 
 
+
 <br>
 
 For prompt ideas visit https://arthub.ai

backends/model_converter/convert_model.py

@@ -42,6 +42,12 @@ def convert_model(checkpoint_filename=None, out_filename=None, torch_weights=No
 
 
  for k in (list(state_dict.keys())):
+
+ if ".encoder." in k or ".decoder." in k:
+ for v , s in [('q' , 'to_q') , ('v' , 'to_v' ) , ('k' , 'to_k') , ('proj_out' , 'to_out.0')]:
+ if f'.{s}.' in k:
+ state_dict[ k.replace(f'.{s}.' , f'.{v}.') ] = state_dict[k]
+
  if '.norm' in k and '.bias' in k:
  k2 = k.replace(".bias" , ".weight")
  k3 = k.replace(".bias" , ".bias_by_weight")
@@ -106,6 +112,15 @@ def convert_model(checkpoint_filename=None, out_filename=None, torch_weights=No
  outfile.write_key(key=k , tensor=np_arr)
 
  outfile.finish_write()
+ sd_version = model_type.replace("_float16" , "").replace("_float32" , "") 
+ if sd_version in ["SD_1x" , "SD_2x"]:
+ sd_type = "sd_model"
+ elif sd_version in ["SD_1x_inpaint" , "SD_2x_inpaint"]:
+ sd_type = "sd_model_inpaint"
+ else:
+ raise ValueError("Invalid sd_version "+ sd_version)
+ model_metadata = {"float_type" : cur_dtype , "sd_type" :sd_version, "type" : sd_type }
+ print("__converted_model_data__" , json.dumps(model_metadata))
 
 
 def usage():

backends/model_converter/sd_shapes.py

@@ -77,7 +77,10 @@ def add_aux_shapes(d):
  "SD_1x_float16": 1012 , 
  "SD_1x_inpaint_float16": 1013 , 
  "SD_1x_just_controlnet_16" : 1014,
- "SD_2x_float16": 1015 }
+ "SD_2x_float16": 1015 ,
+ "sdxl_base_unet_f8_rest_f16" : 3031,
+ }
+
 
 
 extra_keys = ['temb_coefficients_fp32' , 'temb_coefficients_fp16' , 'causal_mask' , 'aux_output_conv.weight' , 'aux_output_conv.bias', 'alphas_cumprod']

backends/model_converter/tdict.py

@@ -22,7 +22,7 @@ def pad_bytes(self, nb):
  self.out_file.write(b'\x00' * nb )
  self.filep += nb
 
- def write_block(self, block_array):
+ def write_block(self, block_array ):
 
  if self.filep %64 != 0:
  npad = 64 - self.filep % 64
@@ -73,7 +73,11 @@ def read_block(self, header_pos, np_shape=None, np_dtype=None):
  block = self.in_file.read(l)
 
  if np_dtype is not None:
- block = np.frombuffer(block, dtype=np_dtype)
+ if "cus_" in np_dtype: #custom dtype, which is not supported by numpy 
+ block = np.frombuffer(block, dtype='uint8')
+ block = decode_custom_dtype(block , np_dtype )
+ else:
+ block = np.frombuffer(block, dtype=np_dtype)
 
  if np_shape is not None:
  block = block.reshape(np_shape)
@@ -145,13 +149,24 @@ def read_key(self , key):
  assert len(ret_arr.tobytes()) == w_idx_len
  return ret_arr.copy()
 
- def write_key(self , key , tensor):
+ def write_key(self , key , tensor, custom_dtype=None ):
  assert key not in self.keys_info
  dtype = str(tensor.dtype)
+ if custom_dtype is not None:
+ dtype = custom_dtype
+ raise not NotImplementedError("Casting not implemented.")
+
  write_info = self.write_block(tensor)
  shape = list(tensor.shape)
  self.keys_info[key] = {"start": write_info['n_start_data'] , "end" : write_info['n_end_data'] , "shape": shape , "dtype" : dtype }
 
+ def write_key_custom_dype(self, uint8_arr , key, custom_dtype , shape ):
+ assert key not in self.keys_info
+ dtype = custom_dtype
+ write_info = self.write_block(uint8_arr)
+ self.keys_info[key] = {"start": write_info['n_start_data'] , "end" : write_info['n_end_data'] , "shape": shape , "dtype" : dtype }
+
+
  def finish_write(self):
 
  if self.filep %64 != 0:

backends/stable_diffusion/control_processors/__init__.py renamed to backends/stable_diffusion/applets/__init__.py

@@ -0,0 +1,58 @@
+import json
+
+def update_state_raw(key , val ):
+ print( "utds " + key + "___U_P_D_A_T_E___" + json.dumps(val))
+
+
+registered_applets = {}
+
+def register_applet(model_container, applet_cls):
+ applet_name = applet_cls.applet_name
+ applet = applet_cls()
+ applet.init_applet(model_container)
+ registered_applets[applet_name] = applet
+
+def run_applet(applet_name , params_dict):
+ registered_applets[applet_name].run(params_dict)
+
+
+class AppletBase:
+
+ applet_name = None
+ applet_title = None
+ is_stop_avail = False
+ applet_description = ""
+ applet_icon = "file"
+ applet_icon_fname = None
+ 
+ def run(self, params):
+ raise NotImplementedError("base cls")
+
+ def get_input_form(self):
+ return []
+ 
+ def update_output( self, key , val ):
+ self.update_state( "outputs." + key , val)
+
+ def update_state(self , key , val ):
+ key = "registered_ext_applets." + self.applet_name + "." + key
+ update_state_raw(key , val)
+
+ def init_applet(self, model_container):
+
+ self.model_container = model_container
+
+ update_state_raw( "registered_ext_applets." + self.applet_name , {})
+ update_state_raw( "registered_ext_applets." + self.applet_name + ".id" , self.applet_name)
+ update_state_raw( "registered_ext_applets." + self.applet_name + ".title" , self.applet_title)
+ update_state_raw( "registered_ext_applets." + self.applet_name + ".description" , self.applet_description)
+ update_state_raw( "registered_ext_applets." + self.applet_name + ".icon" , self.applet_icon )
+ if self.applet_icon_fname is not None:
+ update_state_raw( "registered_ext_applets." + self.applet_name + ".img_icon" , self.applet_icon_fname ) 
+ update_state_raw( "registered_ext_applets." + self.applet_name + ".home_category" , "misc")
+ update_state_raw( "registered_ext_applets." + self.applet_name + ".inputs" , self.get_input_form() )
+ update_state_raw( "registered_ext_applets." + self.applet_name + ".outputs" , [] )
+ update_state_raw( "registered_ext_applets." + self.applet_name + ".is_stop_avail" , self.is_stop_avail )
+
+
+ 

backends/stable_diffusion/applets/applets.py

@@ -0,0 +1,75 @@
+import random
+
+def get_textbox(id, type="str" , default="" , title="" , description=""):
+
+ types = {"str" : "text" , "int" : "number" , "float" : "number"}
+
+ return {
+ "id": str(random.randint(0,19989999)),
+ "component": "InputWithDesc",
+ "title": title,
+ "description":description ,
+ "children": [
+ {
+ "id": id,
+ "component": "Textbox",
+ "placeholder" : "",
+ "default_value" : default ,
+ "type" : types[type],
+ "output_type" :type ,
+ "is_persistant" : False
+ }
+ ]
+ }
+
+def get_output_text(text):
+ return {
+ "id": str(random.randint(0,19989999)),
+ "component": "OutputText",
+ "text" : text
+ }
+def get_output_img(img_path, save_ext='.png' , is_save=False):
+ return {
+ "id": str(random.randint(0,19989999)),
+ "component": "OutputImage",
+ "img_path" : img_path,
+ "is_save" : is_save , 
+ "save_ext" : save_ext 
+ }
+
+def get_file_textbox(id , path_type="", title="" , description="" ):
+ return {
+ "id": str(random.randint(0,19989999)),
+ "component": "InputWithDesc",
+ "full_width": True,
+ "title": title,
+ "description": description,
+ "children": [
+ {
+ "id": id ,
+ "component": "FilePathTextBox",
+ "placeholder" : "",
+ "is_persistant" : False,
+ "path_type" : path_type
+ },
+ ]
+ }
+
+def get_textarea(id , title="" , description="" ):
+ return {
+ "id": str(random.randint(0,19989999)),
+ "component": "InputWithDesc",
+ "full_width": True,
+ "title": title,
+ "description": description,
+ "children": [
+ {
+ "id": id ,
+ "component": "Textarea",
+ "placeholder" : title ,
+ "is_small" : True,
+ "is_persistant" : False,
+ },
+ ]
+ }
+