cofob
/
Eris_api_tensor_patch
forked from Hitmare/Eris_api_tensor_patch
1
0
Fork 0
Code Pull Requests Activity

Upload files to "/"

This commit is contained in:
Hitmare 2023-11-14 19:46:55 +00:00
parent 3d5abcfaca
commit 65471d519b
1 changed files with 128 additions and 4 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

130
api.py
View File

@ -34,6 +34,38 @@ import piexif
import piexif.helper
from contextlib import closing
'''
Eris Bot API modifier
Eris Promptlog:
Every Prompt that is send from through the API will be saved in a Textfile, with the current date as name, in a folder named "logs"
Eris Imagelog:
Every generated Images will be saved in the default "outputs" folder
Eris Consolelog:
Every Prompt that is send from through the API will be displayed in the console/terminal window
Eris TRTpatch:
Necessary modification for the TRT Plugin to work.
Please refer the Readme on https://nextcloud.hitmare.me/index.php/s/D3BmNDDHRXLdxfL for the full TRTpatch instructions
Eris Imagelimit:
Will resize every request down to 1024px max on height and width, keeping the aspect ratio. Also reduces Steps down to 35 if the set Steps exceeds 35
Compatible with the TRTpatch. Please refer the Readme on https://nextcloud.hitmare.me/index.php/s/D3BmNDDHRXLdxfL for the full TRTpatch instructions
To activate any modifications, change the "False" to "True". The capital "T" is important
for example:
eris_imagelog = True
'''
# Eris modifier switches
eris_promtlog = False
eris_imagelog = False
eris_consolelog = False
eris_TRTpatch = False
eris_imagelimit = False
def script_name_to_index(name, scripts):
try:
@ -337,6 +369,40 @@ class Api:
return script_args
def text2imgapi(self, txt2imgreq: models.StableDiffusionTxt2ImgProcessingAPI):
# Eris TRTpacht
if eris_TRTpatch:
txt2imgreq.width = round(txt2imgreq.width / 64) * 64
txt2imgreq.height = round(txt2imgreq.height / 64) * 64
# Eris ______
# Eris imagelimit 1024x1024 35 Steps
if eris_imagelimit:
# Add a check to only resize if the dimensions are larger than 1024
if txt2imgreq.width > 1024 or txt2imgreq.height > 1024:
# Calculate the aspect ratio
aspect_ratio = txt2imgreq.width / txt2imgreq.height
# Scale down to the maximum allowed dimensions while retaining the aspect ratio
if aspect_ratio > 1: # If the image is wider than it is tall
txt2imgreq.width = 1024
txt2imgreq.height = round(1024 / aspect_ratio)
else: # If the image is as wide as it is tall or taller
txt2imgreq.height = 1024
txt2imgreq.width = round(1024 * aspect_ratio)
# Ensure both dimensions are a multiple of 64 (if this is a requirement for your use case)
txt2imgreq.width = round(txt2imgreq.width // 64) * 64
txt2imgreq.height = round(txt2imgreq.height // 64) * 64
# Reduce maximum steps
txt2imgreq.steps = min(txt2imgreq.steps, 35)
# Eris ______
# Eris console prompt log -> writes promts into the console/terminal window
if eris_consolelog:
print('[t2i]', txt2imgreq.width, 'x', txt2imgreq.height, '|', txt2imgreq.prompt)
# Eris ______
script_runner = scripts.scripts_txt2img
if not script_runner.scripts:
script_runner.initialize_scripts(False)
@ -344,7 +410,10 @@ class Api:
if not self.default_script_arg_txt2img:
self.default_script_arg_txt2img = self.init_default_script_args(script_runner)
selectable_scripts, selectable_script_idx = self.get_selectable_script(txt2imgreq.script_name, script_runner)
# Eris save generated images -> will be saved in default outputs folder
if eris_imagelog:
txt2imgreq.save_images = True
# Eris ______
populate = txt2imgreq.copy(update={ # Override __init__ params
"sampler_name": validate_sampler_name(txt2imgreq.sampler_name or txt2imgreq.sampler_index),
"do_not_save_samples": not txt2imgreq.save_images,
@ -362,7 +431,17 @@ class Api:
send_images = args.pop('send_images', True)
args.pop('save_images', None)
# Eris Promtlog -> writing daily log file for txt2img into logs folder
if eris_imagelog:
logfolder = "logs"
if not os.path.exists(logfolder):
os.makedirs(logfolder)
apilogtxt2imgfile = open(f"{logfolder}/{datetime.date.today()}-txt2img.txt", "a")
apilogtxt2imgtext = f"[{datetime.datetime.now()}] Prompt: {txt2imgreq.prompt} | Negative prompt: {txt2imgreq.negative_prompt} | Steps: {txt2imgreq.steps} | Size: {txt2imgreq.width}x{txt2imgreq.height} | CFG: {txt2imgreq.cfg_scale}"
#replace newlines and returns to keep the prompt in one line
apilogtxt2imgtext.replace("\n", " ").replace("\r", " ")
apilogtxt2imgfile.write(f"{apilogtxt2imgtext}\n")
# Eris ______
with self.queue_lock:
with closing(StableDiffusionProcessingTxt2Img(sd_model=shared.sd_model, **args)) as p:
p.is_api = True
@ -387,6 +466,37 @@ class Api:
return models.TextToImageResponse(images=b64images, parameters=vars(txt2imgreq), info=processed.js())
def img2imgapi(self, img2imgreq: models.StableDiffusionImg2ImgProcessingAPI):
# Eris TRTpatch
if eris_TRTpatch:
img2imgreq.width = round(img2imgreq.width / 64) * 64
img2imgreq.height = round(img2imgreq.height / 64) * 64
# Eris ______
# Eris imagelimit 1024x1024 35 Steps
if eris_imagelimit:
# Add a check to only resize if the dimensions are larger than 1024
if img2imgreq.width > 1024 or img2imgreq.height > 1024:
# Calculate the aspect ratio of the input image
aspect_ratio = img2imgreq.width / img2imgreq.height
# Scale down to the maximum allowed dimensions while retaining the aspect ratio
if aspect_ratio > 1: # If the image is wider than it is tall
img2imgreq.width = 1024
img2imgreq.height = round(1024 / aspect_ratio)
else: # If the image is as wide as it is tall or taller
img2imgreq.height = 1024
img2imgreq.width = round(1024 * aspect_ratio)
# Ensure both dimensions are a multiple of 64 (if this is a requirement for your use case)
img2imgreq.width = round(img2imgreq.width / 64) * 64
img2imgreq.height = round(img2imgreq.height / 64) * 64
# Reduce maximum steps
img2imgreq.steps = min(img2imgreq.steps, 35)
# Eris ______
# Eris console prompt log -> writes promts into the console/terminal window
if eris_consolelog:
print('[i2i]', img2imgreq.width, 'x', img2imgreq.height, '|', img2imgreq.prompt)
# Eris ______
init_images = img2imgreq.init_images
if init_images is None:
raise HTTPException(status_code=404, detail="Init image not found")
@ -402,7 +512,10 @@ class Api:
if not self.default_script_arg_img2img:
self.default_script_arg_img2img = self.init_default_script_args(script_runner)
selectable_scripts, selectable_script_idx = self.get_selectable_script(img2imgreq.script_name, script_runner)
# Eris save generated images -> will be saved in default outputs folder
if eris_imagelog:
img2imgreq.save_images = True
# Eris ______
populate = img2imgreq.copy(update={ # Override __init__ params
"sampler_name": validate_sampler_name(img2imgreq.sampler_name or img2imgreq.sampler_index),
"do_not_save_samples": not img2imgreq.save_images,
@ -422,6 +535,17 @@ class Api:
send_images = args.pop('send_images', True)
args.pop('save_images', None)
# Eris Promtlog -> writing daily log file for txt2img into logs folder
if eris_promtlog:
logfolder = "logs"
if not os.path.exists(logfolder):
os.makedirs(logfolder)
apilogimg2imgfile = open(f"{logfolder}/{datetime.date.today()}-img2img.txt", "a")
apilogimg2imgtext = f"[{datetime.datetime.now()}] Prompt: {img2imgreq.prompt} | Negative prompt: {img2imgreq.negative_prompt} | Steps: {img2imgreq.steps} | Size: {img2imgreq.width}x{img2imgreq.height} | CFG: {img2imgreq.cfg_scale} | Denoising: {img2imgreq.denoising_strength}"
#replace newlines and returns to keep the prompt in one line
apilogimg2imgtext.replace("\n", " ").replace("\r", " ")
apilogimg2imgfile.write(f"{apilogimg2imgtext}\n")
# Eris ______
with self.queue_lock:
with closing(StableDiffusionProcessingImg2Img(sd_model=shared.sd_model, **args)) as p: