nodes/ltdrdata-was-node-suite-comfyui
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

History Update

Browse Source 
Add Image History Node
Add history data export to json file for images and whatever else
This commit is contained in:
Jordan Thompson
2023-04-05 23:39:08 -07:00
parent d089ade12e
commit 83d66cb7bd
2 changed files with 102 additions and 17 deletions
Download Patch File Download Diff File Expand all files Collapse all files
.gitignore
+1
View File
@@ -5,3 +5,4 @@ was_suite_settings.json
styles.json
was_suite_config.json
repos/BLIP/
was_history.json
WAS_Node_Suite.py
+101 -17
View File
@@ -48,7 +48,8 @@ CUSTOM_NODES_DIR = ( os.path.dirname(os.path.dirname(NODE_FILE))
else os.path.dirname(NODE_FILE) )
WAS_SUITE_ROOT = os.path.dirname(NODE_FILE)
WAS_DATABASE = os.path.join(WAS_SUITE_ROOT, 'was_suite_settings.json')
WAS_CONFIG = os.path.join(WAS_SUITE_ROOT, 'was_suite_config.json')
WAS_HISTORY_DATABASE = os.path.join(WAS_SUITE_ROOT, 'was_history.json')
WAS_CONFIG_FILE = os.path.join(WAS_SUITE_ROOT, 'was_suite_config.json')
STYLES_PATH = os.path.join(WAS_SUITE_ROOT, 'styles.json')
# WAS Suite Locations Debug
@@ -96,13 +97,14 @@ was_conf_template = {
"webui_styles_persistent_update": True,
"blip_model_url": "https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base_capfilt_large.pth",
"blip_model_vqa_url": "https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base_vqa_capfilt_large.pth",
"history_display_limit": 32,
}
# Create, Load, or Update Config
def getSuiteConfig():
try:
with open(WAS_CONFIG, "r") as f:
with open(WAS_CONFIG_FILE, "r") as f:
was_config = json.load(f)
except OSError as e:
print(e)
@@ -114,7 +116,7 @@ def getSuiteConfig():
def updateSuiteConfig(conf):
try:
with open(WAS_CONFIG, "w", encoding='utf-8') as f:
with open(WAS_CONFIG_FILE, "w", encoding='utf-8') as f:
json.dump(conf, f, indent=4)
except OSError as e:
print(e)
@@ -124,11 +126,11 @@ def updateSuiteConfig(conf):
return False
return True
if not os.path.exists(WAS_CONFIG):
if not os.path.exists(WAS_CONFIG_FILE):
if updateSuiteConfig(was_conf_template):
print(f'\033[34mWAS Node Suite:\033[0m Created default conf file at `{WAS_CONFIG}`.')
print(f'\033[34mWAS Node Suite:\033[0m Created default conf file at `{WAS_CONFIG_FILE}`.')
else:
print(f'\033[34mWAS Node Suite\033[0m Error: Unable to create default conf file at `{WAS_CONFIG}`.')
print(f'\033[34mWAS Node Suite\033[0m Error: Unable to create default conf file at `{WAS_CONFIG_FILE}`.')
else:
was_config = getSuiteConfig()
@@ -255,6 +257,12 @@ class WASDatabase:
except FileNotFoundError:
self.data = {}
def catExists(self, category):
return self.data.__contains__(category)
def keyExists(self, category, key):
return self.data[category].__contains__(key)
def insert(self, category, key, value):
if category not in self.data:
self.data[category] = {}
@@ -1609,7 +1617,7 @@ class WAS_Image_Rescale:
class WAS_Load_Image_Batch:
def __init__(self):
pass
self.HDB = WASDatabase(WAS_HISTORY_DATABASE)
@classmethod
def INPUT_TYPES(cls):
@@ -1629,15 +1637,30 @@ class WAS_Load_Image_Batch:
CATEGORY = "WAS Suite/IO"
def load_batch_images(self, path, pattern='*', index=0, mode="single_image", label='Batch 001'):
if not os.path.exists(path):
return (None, )
fl = self.BatchImageLoader(path, label, pattern)
new_paths = fl.image_paths
if mode == 'single_image':
image = fl.get_image_by_id(index)
else:
image = fl.get_next_image()
self.image = image
if ( self.HDB.catExists("History")
and self.HDB.keyExists("History", "Images") ):
saved_paths = self.HDB.get("History", "Images")
for path in saved_paths:
if not os.path.exists(path):
saved_paths.remove(path)
saved_paths.extend(new_paths)
self.HDB.update("History", "Images", saved_paths)
else:
if not self.HDB.catExists("History"):
self.HDB.insertCat("History")
self.HDB.insert("History", "Images", new_paths)
return (pil2tensor(image), )
@@ -1685,6 +1708,51 @@ class WAS_Load_Image_Batch:
@classmethod
def IS_CHANGED(cls, **kwargs):
return float("NaN")
# IMAGE HISTORY NODE
class WAS_Image_History:
def __init__(self):
self.HDB = WASDatabase(WAS_HISTORY_DATABASE)
self.conf = getSuiteConfig()
@classmethod
def INPUT_TYPES(cls):
HDB = WASDatabase(WAS_HISTORY_DATABASE)
conf = getSuiteConfig()
paths = ['No History']
if HDB.catExists("History") and HDB.keyExists("History", "Images"):
history_paths = HDB.get("History", "Images")
if conf.__contains__('history_display_limit'):
history_paths = history_paths[-conf['history_display_limit']:]
paths = []
for path in history_paths:
paths.append(os.path.join('...'+os.sep+os.path.basename(os.path.dirname(path)), os.path.basename(path)))
return {
"required": {
"image": (paths,),
},
}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "image_history"
CATEGORY = "WAS Suite/History"
def image_history(self, image):
self.HDB = WASDatabase(WAS_HISTORY_DATABASE)
paths = {}
if self.HDB.catExists("History") and self.HDB.keyExists("History", "Images"):
history_paths = self.HDB.get("History", "Images")
for path in history_paths:
paths.update({os.path.join('...'+os.sep+path.basename(os.path.dirname(path)), os.path.basename(path)): path})
if os.path.exists(paths[image]) and paths.__contains__(image):
return (pil2tensor(Image.open(paths[image]).convert('RGB')), )
else:
raise ValueError(f"\033[34mWAS NS\033[0m Error: The image `{image}` does not exist!")
return (pil2tensor(Image.new('RGB', (512,512), (0, 0, 0, 0))), )
# IMAGE PADDING
@@ -3569,8 +3637,8 @@ class WAS_KSampler:
def INPUT_TYPES(cls):
return {"required":
{"model": ("MODEL",),
"seed": ("SEED",),
{"model": ("MODEL", ),
"seed": ("SEED", ),
"steps": ("INT", {"default": 20, "min": 1, "max": 10000}),
"cfg": ("FLOAT", {"default": 8.0, "min": 0.0, "max": 100.0}),
"sampler_name": (comfy.samplers.KSampler.SAMPLERS, ),
@@ -3589,6 +3657,7 @@ class WAS_KSampler:
def sample(self, model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=1.0):
return nodes.common_ksampler(model, seed['seed'], steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise)
# SEED NODE
@@ -4237,7 +4306,6 @@ class WAS_BLIP_Analyze_Image:
or 'transformers' not in packages()
or 'GitPython' not in packages()
or 'fairscale' not in packages() ):
print(packages())
print("\033[34mWAS NS:\033[0m Installing BLIP dependencies...")
subprocess.check_call([sys.executable, '-m', 'pip', '-q', 'install', 'transformers==4.26.1', 'timm>=0.4.12', 'gitpython', 'fairscale>=0.4.4'])
@@ -4257,7 +4325,7 @@ class WAS_BLIP_Analyze_Image:
pass
sys.modules["fairscale.nn.checkpoint.checkpoint_activations"] = FakeFairscale
def transformImage(input_image, image_size, device):
def transformImage_legacy(input_image, image_size, device):
raw_image = input_image.convert('RGB')
raw_image = raw_image.resize((image_size, image_size))
transform = transforms.Compose([
@@ -4267,6 +4335,17 @@ class WAS_BLIP_Analyze_Image:
])
image = transform(raw_image).unsqueeze(0).to(device)
return image
def transformImage(input_image, image_size, device):
raw_image = input_image.convert('RGB')
raw_image = raw_image.resize((image_size, image_size))
transform = transforms.Compose([
transforms.Resize(raw_image.size, interpolation=InterpolationMode.BICUBIC),
transforms.ToTensor(),
transforms.Normalize((0.48145466, 0.4578275, 0.40821073), (0.26862954, 0.26130258, 0.27577711))
])
image = transform(raw_image).unsqueeze(0).to(device)
return image.view(1, -1, image_size, image_size) # Change the shape of the output tensor
sys.path.append(os.path.join(WAS_SUITE_ROOT, 'repos'+os.sep+'BLIP'))
@@ -4278,13 +4357,18 @@ class WAS_BLIP_Analyze_Image:
conf = getSuiteConfig()
image = tensor2pil(image)
size = 384
tensor = transformImage(image, size, device)
if 'transformers==4.26.1' in packages(True):
print("Using Legacy `transformImaage()`")
tensor = transformImage_legacy(image, size, device)
else:
tensor = transformImage(image, size, device)
if mode == 'caption':
from models.blip import blip_decoder
blip_dir = os.path.join(os.getcwd()+os.sep+'ComfyUI', 'models'+os.sep+'blip')
blip_dir = os.path.join(( os.getcwd()+os.sep+'ComfyUI' if not os.getcwd().startswith('/content') else os.getcwd() ), 'models'+os.sep+'blip')
if not os.path.exists(blip_dir):
os.mkdir(blip_dir)
@@ -4310,7 +4394,7 @@ class WAS_BLIP_Analyze_Image:
from models.blip_vqa import blip_vqa
blip_dir = os.path.join(os.getcwd()+os.sep+'ComfyUI', 'models'+os.sep+'blip')
blip_dir = os.path.join(( os.getcwd()+os.sep+'ComfyUI' if not os.getcwd().startswith('/content') else os.getcwd() ), 'models'+os.sep+'blip')
if not os.path.exists(blip_dir):
os.mkdir(blip_dir)
@@ -4319,7 +4403,7 @@ class WAS_BLIP_Analyze_Image:
if conf.__contains__('blip_model_vqa_url'):
model_url = conf['blip_model_vqa_url']
else:
model_url = 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base_capfilt_large.pth'
model_url = 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base_vqa_capfilt_large.pth'
model = blip_vqa(pretrained=model_url, image_size=size, vit='base')
model.eval()
@@ -4718,7 +4802,6 @@ class WAS_Debug_Number_to_Console:
def IS_CHANGED(cls, **kwargs):
return float("NaN")
# NODE MAPPING
NODE_CLASS_MAPPINGS = {
"CLIPTextEncode (NSP)": WAS_NSP_CLIPTextEncoder,
@@ -4741,6 +4824,7 @@ NODE_CLASS_MAPPINGS = {
"Image Gradient Map": WAS_Image_Gradient_Map,
"Image Generate Gradient": WAS_Image_Generate_Gradient,
"Image High Pass Filter": WAS_Image_High_Pass_Filter,
"Image History Loader": WAS_Image_History,
"Image Levels Adjustment": WAS_Image_Levels,
"Image Load": WAS_Load_Image,
"Image Median Filter": WAS_Image_Median_Filter,