import os import sys import uuid import time import argparse import numpy as np from PIL import Image import mc_render import gpt_image from build_target_img import check_skin, ensure_valid_skin from alice_to_steve import alice_to_steve from mc_voxel_texture_resolver import resolve_voxel_consistency def main(): parser = argparse.ArgumentParser( description="Render Minecraft skin to 3D views and call the img2img model with base64 references." ) parser.add_argument("skin", help="Path to local Minecraft skin image file.") parser.add_argument("-o", "--output", help="Output path for the generated image. Defaults to 'result_.png'.") parser.add_argument("-p", "--prompt", default="生成ta的全身真人照片,再生成ta的背面放在图片右边。请准确还原人物的特征细节,注意真人照片里面通常不包含像素风格的装饰。", help="Prompt for the img2img model.") parser.add_argument( "-r", "--render-only", action="store_true", help="Only render the 3D front and back views locally, without calling img2img.", ) args = parser.parse_args() # 1. Validate skin path if not os.path.exists(args.skin): print(f"Error: Skin file '{args.skin}' does not exist.") sys.exit(1) # 2. Process/Validate the skin image (Alex/Steve conversion, validity, consistency) try: print(f"[*] Processing skin file: {args.skin}") skin_image = Image.open(args.skin).convert('RGBA') valid, is_alex = check_skin(skin_image) if not valid: print(f"Error: Skin '{args.skin}' fails validation.") sys.exit(1) if is_alex: print("[*] Detected Alex skin. Converting to Steve...") skin_image = alice_to_steve(skin_image) skin_image = ensure_valid_skin(skin_image) skin_image = resolve_voxel_consistency(skin_image) except Exception as e: print(f"[!] Skin processing failed: {e}") sys.exit(1) # 3. Generate front and back 3D renders using mc_render pos_args2 = { 'head': (0, 28, 0), 'body': (0, 18, 0), 'right_arm': (-6, 18, 0), 'left_arm': (6, 18, 0), 'right_leg': (-2, 6, 0), 'left_leg': (2, 6, 0), } # Determine output filenames for renders if args.render_only: if args.output: base, ext = os.path.splitext(args.output) temp_front_path = f"{base}_front{ext or '.png'}" temp_back_path = f"{base}_back{ext or '.png'}" else: temp_front_path = "render_front.png" temp_back_path = "render_back.png" else: # Generate unique filenames for temp renders unique_id = uuid.uuid4() temp_front_path = f"temp_front_{unique_id}.png" temp_back_path = f"temp_back_{unique_id}.png" try: print("[*] Rendering skin 3D front view...") mc_render.render_skin( skin=np.array(skin_image), output_size=(768, 768), cam_front=(0.25, 0.25, 0.25), use_voxels=False, ortho=False, save_path=temp_front_path, transparent_background=True, zoom=0.3, look_at_y=18, pos_args=pos_args2, off_screen=True ) print("[*] Rendering skin 3D back view...") mc_render.render_skin( skin=np.array(skin_image), output_size=(768, 768), cam_front=(-0.25, 0.25, -0.25), use_voxels=False, ortho=False, save_path=temp_back_path, transparent_background=True, zoom=0.3, look_at_y=18, pos_args=pos_args2, off_screen=True ) if args.render_only: print(f"[+] Render-only mode active. Views saved to:\n - {temp_front_path}\n - {temp_back_path}") return # 4. Invoke gpt_image.generate_img2img print("[*] Invoking image-to-image pipeline via gpt_image...") output_file = gpt_image.generate_img2img( local_image_paths=[temp_front_path, temp_back_path], prompt=args.prompt, output_path=args.output ) print(f"[+] Pipeline completed successfully. Output saved to: {output_file}") except Exception as e: print(f"[!] Execution failed: {e}") sys.exit(1) finally: # Clean up local temporary files if not in render-only mode if not args.render_only: for temp_file in [temp_front_path, temp_back_path]: if os.path.exists(temp_file): print(f"[*] Removing local temporary file: {temp_file}") try: os.remove(temp_file) except Exception as e: print(f"[!] Failed to remove local file {temp_file}: {e}") if __name__ == '__main__': main()