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import os
from datetime import datetime
from diffusers import StableDiffusionPipeline, StableDiffusionLDM3DPipeline
streetview_path="streetview-v4-10000-images.safetensors"
sd_diffusers_path = "checkpoints/v2-1_768-nonema-pruned.safetensors"
ldm3d_path = "checkpoints/ldm3d-pano"
prompt_file_path = "prompts/combined_prompts_plain.txt"
num_inference_steps= 50
sample_basename = "streetview"
n_prompt = "bad, deformed, ugly, low quality, underexposed, overexposed, grainy, cartoon, anime"
original_config_file="v2-inference-v.yaml"
HEIGHT = 768
WIDTH = 2 * HEIGHT
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
output_directory = f'Generated Images/ldm3d'
# Create the directory if it does not exist
os.makedirs(output_directory, exist_ok=True)
# streetview and sd21
#pipe = StableDiffusionPipeline.from_single_file(streetview_path, use_auth_token=False, local_files_only=True, original_config_file=original_config_file)
#ldm3d-pano
pipe = StableDiffusionLDM3DPipeline.from_pretrained(ldm3d_path, use_auth_token=False, local_files_only=True, original_config_file=original_config_file)
pipe = pipe.to("cuda")
with open(prompt_file_path, 'r') as file:
prompts = file.readlines()
for i, prompt in enumerate(prompts, start=1):
prompt = prompt.strip()
sample_name = f"{i}_{prompt}_{HEIGHT}_{WIDTH}.png"
save_path = os.path.join(output_directory, sample_name)
# streetview and sd21
#image = pipe(prompt=prompt, num_inference_steps=num_inference_steps, negative_prompt=n_prompt, height=HEIGHT, width=WIDTH).images[0]
# ldm3d
image = pipe(prompt=prompt, num_inference_steps=num_inference_steps, negative_prompt=n_prompt, height=HEIGHT, width=WIDTH).rgb[0]
image.save(save_path)
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