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Running
on
Zero
Running
on
Zero
File size: 4,324 Bytes
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import os
import argparse
import json
from PIL import Image
import openai
from tenacity import retry, wait_exponential, stop_after_attempt, retry_if_exception_type
from utils import encode_image_to_datauri, cot_with_gpt, extract_instructions, infer_with_DiT, roi_localization, fusion
def main():
parser = argparse.ArgumentParser(description="Evaluate single image + instruction using GPT-4o")
parser.add_argument("image_path", help="Path to input image")
parser.add_argument("json_path", help="Path to JSON file containing categories and instructions")
args = parser.parse_args()
openai.api_key = "YOUR_API_KEY"
if not openai.api_key:
raise ValueError("OPENAI_API_KEY environment variable not set.")
os.makedirs("results", exist_ok=True)
#######################################################
### Load instructions from JSON ###
#######################################################
try:
with open(args.json_path, 'r') as f:
data = json.load(f)
categories = data.get('categories', [])
instructions = data.get('instructions', [])
if not categories or not instructions:
raise ValueError("JSON file must contain 'categories' and 'instructions' arrays.")
if len(categories) != len(instructions):
raise ValueError("Length of 'categories' and 'instructions' must match.")
print("Loaded instructions from JSON:")
for i, (cat, instr) in enumerate(zip(categories, instructions)):
print(f"Step {i+1}: [{cat}] {instr}")
except Exception as e:
raise ValueError(f"Failed to load JSON file: {str(e)}")
###################################################
### Neural Program Interpreter ###
###################################################
for i in range(len(categories)):
if i == 0:
image = args.image_path
else:
image = f"results/{i-1}.png"
category = categories[i]
instruction = instructions[i]
if category in ('Add', 'Remove', 'Replace', 'Action Change', 'Move', 'Resize'):
if category in ('Add', 'Remove', 'Replace'):
if category == 'Add':
edited_image = infer_with_DiT('RoI Editing', image, instruction, category)
else:
mask_image = roi_localization(image, instruction, category)
edited_image = infer_with_DiT('RoI Inpainting', mask_image, instruction, category)
elif category == 'Action Change':
mask_image = roi_localization(image, instruction, category)
edited_image = infer_with_DiT('RoI Inpainting', mask_image, instruction, 'Remove')
changed_instance, x0, y1, scale = infer_with_DiT('RoI Editing', image, instruction, category)
fusion_image = fusion(edited_image, changed_instance, x0, y1, scale)
edited_image = infer_with_DiT('RoI Compositioning', fusion_image, instruction, None)
elif category in ('Move', 'Resize'):
mask_image, changed_instance, x0, y1, scale = roi_localization(image, instruction, category)
edited_image = infer_with_DiT('RoI Inpainting', mask_image, instruction, 'Remove')
fusion_image = fusion(edited_image, changed_instance, x0, y1, scale)
fusion_image.save("fusion.png")
edited_image = infer_with_DiT('RoI Compositioning', fusion_image, instruction, None)
elif category in ('Appearance Change', 'Background Change', 'Color Change', 'Material Change', 'Expression Change'):
edited_image = infer_with_DiT('RoI Editing', image, instruction, category)
elif category in ('Tone Transfer', 'Style Change'):
edited_image = infer_with_DiT('Global Transformation', image, instruction, category)
else:
raise ValueError(f"Invalid category: '{category}'")
image = edited_image
image.save(f"results/{i}.png")
print(f"Step {i+1} completed: {category} - {instruction}")
if __name__ == "__main__":
main() |