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| import argparse | |
| import numpy as np | |
| from nltk.translate.bleu_score import sentence_bleu | |
| from minigpt4.common.registry import registry | |
| from minigpt4.common.config import Config | |
| # imports modules for registration | |
| from minigpt4.datasets.builders import * | |
| from minigpt4.models import * | |
| from minigpt4.processors import * | |
| from minigpt4.runners import * | |
| from minigpt4.tasks import * | |
| def eval_parser(): | |
| parser = argparse.ArgumentParser(description="Demo") | |
| parser.add_argument("--cfg-path", required=True, help="path to configuration file.") | |
| parser.add_argument("--name", type=str, default='A2', help="evaluation name") | |
| parser.add_argument("--ckpt", type=str, help="path to configuration file.") | |
| parser.add_argument("--eval_opt", type=str, default='all', help="path to configuration file.") | |
| parser.add_argument("--max_new_tokens", type=int, default=10, help="max number of generated tokens") | |
| parser.add_argument("--batch_size", type=int, default=32) | |
| parser.add_argument("--lora_r", type=int, default=64, help="lora rank of the model") | |
| parser.add_argument("--lora_alpha", type=int, default=16, help="lora alpha") | |
| parser.add_argument( | |
| "--options", | |
| nargs="+", | |
| help="override some settings in the used config, the key-value pair " | |
| "in xxx=yyy format will be merged into config file (deprecate), " | |
| "change to --cfg-options instead.", | |
| ) | |
| return parser | |
| def prepare_texts(texts, conv_temp): | |
| convs = [conv_temp.copy() for _ in range(len(texts))] | |
| [conv.append_message( | |
| conv.roles[0], '<Img><ImageHere></Img> {}'.format(text)) for conv, text in zip(convs, texts)] | |
| [conv.append_message(conv.roles[1], None) for conv in convs] | |
| texts = [conv.get_prompt() for conv in convs] | |
| return texts | |
| def init_model(args): | |
| print('Initialization Model') | |
| cfg = Config(args) | |
| # cfg.model_cfg.ckpt = args.ckpt | |
| # cfg.model_cfg.lora_r = args.lora_r | |
| # cfg.model_cfg.lora_alpha = args.lora_alpha | |
| model_config = cfg.model_cfg | |
| model_cls = registry.get_model_class(model_config.arch) | |
| model = model_cls.from_config(model_config).to('cuda:0') | |
| # import pudb; pudb.set_trace() | |
| key = list(cfg.datasets_cfg.keys())[0] | |
| vis_processor_cfg = cfg.datasets_cfg.get(key).vis_processor.train | |
| vis_processor = registry.get_processor_class(vis_processor_cfg.name).from_config(vis_processor_cfg) | |
| print('Initialization Finished') | |
| return model, vis_processor | |
| def computeIoU(bbox1, bbox2): | |
| x1, y1, x2, y2 = bbox1 | |
| x3, y3, x4, y4 = bbox2 | |
| intersection_x1 = max(x1, x3) | |
| intersection_y1 = max(y1, y3) | |
| intersection_x2 = min(x2, x4) | |
| intersection_y2 = min(y2, y4) | |
| intersection_area = max(0, intersection_x2 - intersection_x1 + 1) * max(0, intersection_y2 - intersection_y1 + 1) | |
| bbox1_area = (x2 - x1 + 1) * (y2 - y1 + 1) | |
| bbox2_area = (x4 - x3 + 1) * (y4 - y3 + 1) | |
| union_area = bbox1_area + bbox2_area - intersection_area | |
| iou = intersection_area / union_area | |
| return iou | |