|
|
| import os |
| import json |
| from PIL import Image |
| from tqdm import tqdm |
| from pydash import at |
| from mathruler.grader import extract_boxed_content |
| from ..question_formats import get_judgement_prompt,get_multiple_choice_prompt |
| from ..utils import save_json,extract,judge_multi_choice,judge_close_end_vqa,judge_judgement |
| from ..base_dataset import BaseDataset |
|
|
| class Radrestruct(BaseDataset): |
| def __init__(self,model,dataset_path,output_path): |
| self.model = model |
| self.output_path = output_path |
| self.dataset_path = dataset_path |
| self.samples = [] |
| self.chunk_idx = int(os.environ.get("chunk_idx",0)) |
| self.num_chunks = int(os.environ.get("num_chunks",1)) |
| |
|
|
| |
| def load_data(self): |
| dataset_path = self.dataset_path |
| id_to_img_mapping_path = os.path.join(dataset_path,"id_to_img_mapping_frontal_reports.json") |
| reports_path = os.listdir(os.path.join(dataset_path,"test_qa_pairs")) |
| answer_options_path = os.path.join(dataset_path,"answer_options.json") |
|
|
|
|
| dataset = [] |
|
|
| with open(id_to_img_mapping_path, "r") as f: |
| id_to_img_mapping_frontal_reports = json.load(f) |
|
|
| |
| for report_file in reports_path: |
| for elem in id_to_img_mapping_frontal_reports[report_file.split(".")[0]]: |
| dataset.append((report_file,elem)) |
|
|
| with open(answer_options_path, "r") as f: |
| answer_options = json.load(f) |
|
|
| |
| for idx,sample in tqdm(enumerate(dataset)): |
| if idx % self.num_chunks == self.chunk_idx: |
| samples = self.construct_messages(sample,answer_options) |
| self.samples.extend(samples) |
| return self.samples |
|
|
| def construct_messages(self,sample,answer_options): |
| report,img = sample |
| report_id = report.split(".")[0] |
| img_path = os.path.join(self.dataset_path,"imgs",f"{img}.png") |
| img = Image.open(img_path).convert("RGB") |
|
|
| sample = {} |
| samples = [] |
| with open(os.path.join(self.dataset_path,"test_qa_pairs",report), "r") as f: |
| qa_pairs = json.load(f) |
| |
| for qa_pair_idx,qa_pair in enumerate(qa_pairs): |
| question,answer,history,info = qa_pair |
| options = info["options"] |
| answer_idxs = at(answer_options,*options) |
| answer_type = info["answer_type"] |
| |
| is_reasoning = True if os.environ.get("REASONING","False") == "True" else False |
| if answer_type == "single_choice": |
| prompt = get_judgement_prompt(question,is_reasoning) |
| else: |
| prompt = get_multiple_choice_prompt(question,options,is_reasoning) |
| messages = {"prompt":prompt,"image":img} |
| sample["messages"] = messages |
| sample["answer_type"] = answer_type |
| sample["question"] = question |
| sample["choices"] = options |
| sample["answer"] = answer[0] |
| samples.append(sample) |
| return samples |
|
|
|
|
| def cal_metrics(self,out_samples): |
| metrics = { |
| "total metrics" : { |
| "total":0, |
| "right":0 |
| }, |
| "single_choice" : { |
| "total" : 0, |
| "right" : 0 |
| }, |
| "multiple_choice" : { |
| "total" : 0, |
| "right" : 0 |
| } |
| } |
|
|
| for i,out_sample in tqdm(enumerate(out_samples)): |
| response = out_sample["response"] |
| if extract_boxed_content(response)!= "None": |
| response = extract_boxed_content(response) |
| elif "<answer>" in response: |
| response = extract(response,"answer") |
|
|
| answer = out_sample["answer"] |
| question = out_sample["question"] |
| answer_type = out_sample["answer_type"] |
| choices = out_sample["choices"] |
| answer = answer.lower().strip() |
| response = response.lower().strip() |
|
|
| metrics["total metrics"]["total"] += 1 |
| if answer_type == "single_choice": |
| metrics["single_choice"]["total"] += 1 |
| correct = judge_judgement(answer,response) |
| out_samples[i]["correct"] = correct |
| if correct: |
| metrics["single_choice"]["right"] += 1 |
| metrics["total metrics"]["right"] += 1 |
| else: |
| metrics["multiple_choice"]["total"] += 1 |
| correct = judge_multi_choice(choices,answer,response) |
| out_samples[i]["correct"] = correct |
| if correct: |
| metrics["multiple_choice"]["right"] += 1 |
| metrics["total metrics"]["right"] += 1 |
|
|
| metrics["total metrics"]["acc"] = metrics["total metrics"]["right"]/metrics["total metrics"]["total"] |
| metrics["single_choice"]["acc"] = metrics["single_choice"]["right"]/metrics["single_choice"]["total"] |
| metrics["multiple_choice"]["acc"] = metrics["multiple_choice"]["right"]/metrics["multiple_choice"]["total"] |
|
|
| return metrics,out_samples |
|
|
