prediction.py

from dataloader import CellLoader

def run_sequence_prediction(
 sequence_input,
 nucleus_image,
 protein_image,
 model,
 device
):
 """
 Run Celle model with provided inputs and display results.

 :param sequence: Path to sequence file
 :param nucleus_image_path: Path to nucleus image
 :param protein_image_path: Path to protein image (optional)
 :param model_ckpt_path: Path to model checkpoint
 :param model_config_path: Path to model config
 """
 
 # Instantiate dataset object
 dataset = CellLoader(
 sequence_mode="embedding",
 vocab="esm2",
 split_key="val",
 crop_method="center",
 resize=600,
 crop_size=256,
 text_seq_len=1000,
 pad_mode="end",
 threshold="median",
 )

 # Check if sequence is provided and valid
 if len(sequence_input) == 0:
 raise ValueError("Sequence must be provided.")

 if "<mask>" not in sequence_input:
 print("Warning: Sequence does not contain any masked positions to predict.")

 # Convert SEQUENCE to sequence using dataset.tokenize_sequence()
 sequence = dataset.tokenize_sequence(sequence_input)

 # Sample from model using provided sequence and nucleus image
 _, predicted_sequence, _ = model.celle.sample_text(
 text=sequence.to(device),
 condition=nucleus_image.to(device),
 image=protein_image.to(device),
 force_aas=True,
 temperature=1,
 progress=False,
 )
 
 os.chdir(base_dir)

 return predicted_sequence