This commit is contained in:
Marc-Andre Ferland 2022-10-19 00:26:09 -04:00
commit 0da0c6bd77

View File

@ -289,6 +289,7 @@ def get_base_path(disk_path, session_id, prompt, img_id, ext, suffix=None):
os.makedirs(session_out_path, exist_ok=True)
prompt_flattened = filename_regex.sub('_', prompt)[:50]
if suffix is not None:
return os.path.join(session_out_path, f"{prompt_flattened}_{img_id}_{suffix}.{ext}")
@ -387,8 +388,7 @@ def do_mk_img(req: Request):
opt_f = 8
opt_ddim_eta = 0.0
opt_init_img = req.init_image
img_id = base64.b64encode(int(time.time()).to_bytes(8, 'big')).decode() # Generate unique ID based on time.
img_id = img_id.translate({43:None, 47:None, 61:None})[-8:] # Remove + / = and keep last 8 chars.
print(req.to_string(), '\n device', thread_data.device)
print('\n\n Using precision:', thread_data.precision)
@ -533,6 +533,8 @@ def do_mk_img(req: Request):
print("saving images")
for i in range(batch_size):
img_id = base64.b64encode(int(time.time()+i).to_bytes(8, 'big')).decode() # Generate unique ID based on time.
img_id = img_id.translate({43:None, 47:None, 61:None})[-8:] # Remove + / = and keep last 8 chars.
x_samples_ddim = thread_data.modelFS.decode_first_stage(x_samples[i].unsqueeze(0))
x_sample = torch.clamp((x_samples_ddim + 1.0) / 2.0, min=0.0, max=1.0)