From 8a2a831c80b67e595f419ad8ec1abbf30c6f4802 Mon Sep 17 00:00:00 2001
From: hodanov <1031hoda@gmail.com>
Date: Mon, 4 Nov 2024 08:53:43 +0900
Subject: [PATCH] Remove cmd/sd15_txt2img.py. Rename cmd/sdxl_txt2img.py ->
 cmd/txt2img_handler.p.

---
 cmd/sd15_txt2img.py                         | 72 ---------------------
 cmd/{sdxl_txt2img.py => txt2img_handler.py} |  0
 2 files changed, 72 deletions(-)
 delete mode 100644 cmd/sd15_txt2img.py
 rename cmd/{sdxl_txt2img.py => txt2img_handler.py} (100%)

diff --git a/cmd/sd15_txt2img.py b/cmd/sd15_txt2img.py
deleted file mode 100644
index dcd38c7..0000000
--- a/cmd/sd15_txt2img.py
+++ /dev/null
@@ -1,72 +0,0 @@
-import logging
-import time
-
-import domain
-import modal
-
-app = modal.App("run-stable-diffusion-cli")
-run_inference = modal.Function.from_name(
-    "stable-diffusion-cli",
-    "SD15.run_txt2img_inference",
-)
-
-
-@app.local_entrypoint()
-def main(
-    prompt: str,
-    n_prompt: str,
-    height: int = 512,
-    width: int = 512,
-    samples: int = 5,
-    steps: int = 20,
-    seed: int = -1,
-    use_upscaler: str = "",
-    fix_by_controlnet_tile: str = "False",
-    output_format: str = "png",
-) -> None:
-    """main() is the entrypoint for the Runway CLI.
-    This pass the given prompt to StableDiffusion on Modal, gets back a list of images and outputs images to local.
-    """
-    logging.basicConfig(
-        level=logging.INFO,
-        format="[%(levelname)s] %(asctime)s - %(message)s",
-        datefmt="%Y-%m-%d %H:%M:%S",
-    )
-    logger = logging.getLogger("run-stable-diffusion-cli")
-
-    output_directory = domain.OutputDirectory()
-    directory_path = output_directory.make_directory()
-    logger.info("Made a directory: %s", directory_path)
-
-    prompts = domain.Prompts(prompt, n_prompt, height, width, samples, steps)
-    sd_output_manager = domain.StableDiffusionOutputManger(prompts, directory_path)
-    for sample_index in range(samples):
-        new_seed = domain.Seed(seed)
-        start_time = time.time()
-        images = run_inference.remote(
-            prompt=prompt,
-            n_prompt=n_prompt,
-            height=height,
-            width=width,
-            batch_size=1,
-            steps=steps,
-            seed=new_seed.value,
-            use_upscaler=use_upscaler == "True",
-            fix_by_controlnet_tile=fix_by_controlnet_tile == "True",
-            output_format=output_format,
-        )
-        for generated_image_index, image_bytes in enumerate(images):
-            saved_path = sd_output_manager.save_image(
-                image_bytes,
-                new_seed.value,
-                sample_index,
-                generated_image_index,
-                output_format,
-            )
-            logger.info("Saved image to the: %s", saved_path)
-
-        total_time = time.time() - start_time
-        logger.info("Sample %s, took %ss (%ss / image).", sample_index, total_time, (total_time) / len(images))
-
-    saved_prompts_path = sd_output_manager.save_prompts()
-    logger.info("Saved prompts: %s", saved_prompts_path)
diff --git a/cmd/sdxl_txt2img.py b/cmd/txt2img_handler.py
similarity index 100%
rename from cmd/sdxl_txt2img.py
rename to cmd/txt2img_handler.py