start pipeline script dynamically calculates absolute paths

3d-generation-pipeline/start_pipeline.py

@@ -2,6 +2,7 @@ import os
 import base64
 import requests
 import argparse
+from pathlib import Path
 from datetime import datetime
 from dotenv import load_dotenv
 
@@ -15,7 +16,7 @@ def get_timestamp():
     return datetime.now().strftime("%Y-%m-%d-%H-%M-%S")
 
 
-def text_to_image(prompt, output_name):
+def text_to_image(prompt, output_path):
     MODEL = "@cf/black-forest-labs/flux-1-schnell"
     URL = f"https://api.cloudflare.com/client/v4/accounts/{ACCOUNT_ID}/ai/run/{MODEL}"
 
@@ -38,11 +39,9 @@ def text_to_image(prompt, output_name):
 
     img_bytes = base64.b64decode(b64)
 
-    out_path = f"images/{output_name}.jpg"
-    with open(out_path, "wb") as f:
+    with open(output_path, "wb") as f:
         f.write(img_bytes)
 
-    return out_path
 
 def refine_text_prompt(prompt):
     MODEL = "@cf/meta/llama-3.2-3b-instruct"
@@ -70,7 +69,8 @@ def refine_text_prompt(prompt):
 def image_to_3d(image_path, output_path):
     import subprocess
 
-    MODEL_FOLDER = r"D:\users\henrisel\stable-fast-3d"
+    # TODO: make this configurable
+    MODEL_FOLDER = r"D:\henrisel\AI-models\stable-fast-3d"
 
     venv_python = MODEL_FOLDER + r"\.venv\Scripts\python.exe"
     script_path = MODEL_FOLDER + r"\run.py"
@@ -99,11 +99,13 @@ def main():
     print(f"User prompt: {user_prompt}")
     refined_prompt = refine_text_prompt(user_prompt)
     print(f"Refined prompt: {refined_prompt}")
-    image_path = text_to_image(refined_prompt, get_timestamp())
+    timestamp = get_timestamp()
+    image_path = Path.cwd() / "images" / f"{timestamp}.jpg"
+    text_to_image(refined_prompt, image_path)
     print(f"Generated image file: {image_path}")
-    output_path = r"\models"
-    image_to_3d(image_path, output_path)
-    print(f"Generated 3D model file: {output_path}")
+    model_path = Path.cwd() / "models" / timestamp
+    image_to_3d(image_path, model_path)
+    print(f"Generated 3D model file: {model_path}")
 
 
 if __name__ == "__main__":