Download spatial-model/VLM-3R/scripts/summarize_data.py from hyin-ustc/embodied-eval: direct link, hf CLI and curl.
- Browser
- Download file 2.83 kB
-
https://huggingface.co/datasets/hyin-ustc/embodied-eval/resolve/main/spatial-model/VLM-3R/scripts/summarize_data.py
- Command line
-
hf download hf://datasets/hyin-ustc/embodied-eval/spatial-model/VLM-3R/scripts/summarize_data.py
-
curl -L -o summarize_data.py https://huggingface.co/datasets/hyin-ustc/embodied-eval/resolve/main/spatial-model/VLM-3R/scripts/summarize_data.py
2.83 kB
| import json | |
| import os | |
| from tqdm import tqdm | |
| with open("/mnt/bn/vl-research/workspace/boli01/zzzprojects/LLaVA/playground/data/llava_v1_5_mix665k.json") as f: | |
| llava_v1_5_mix665k = json.load(f) # 665298 | |
| with open("/mnt/bn/vl-research/workspace/boli01/zzzprojects/LLaVA/playground/data/llava_instruct_150k.json") as f: | |
| llava_instruct_150k = json.load(f) # 157712 | |
| # Create sets of "id" fields | |
| mix665k_ids = set() | |
| for item in llava_v1_5_mix665k: | |
| all_conv = "" | |
| for cur_conversation in item["conversations"]: | |
| all_conv += cur_conversation["value"] | |
| mix665k_ids.add(f'{item["id"]}_{all_conv}') | |
| instruct_150k_ids = set() | |
| for item in llava_instruct_150k: | |
| all_conv = "" | |
| for cur_conversation in item["conversations"]: | |
| all_conv += cur_conversation["value"] | |
| instruct_150k_ids.add(f'{item["id"]}_{all_conv}') | |
| share_gpt_ids = set() | |
| for item in llava_v1_5_mix665k: | |
| if "image" not in item: | |
| all_conv = "" | |
| for cur_conversation in item["conversations"]: | |
| all_conv += cur_conversation["value"] | |
| share_gpt_ids.add(f'{item["id"]}_{all_conv}') # 40688 | |
| # Get "id" fields that are in mix665k but not in instruct_150k and share_gpt | |
| new_ids = mix665k_ids - instruct_150k_ids - share_gpt_ids # 466898 | |
| # Get "id" fields that are in mix665k but not in share_gpt | |
| # new_ids = mix665k_ids - share_gpt_ids #624610 | |
| # import pdb; pdb.set_trace() | |
| # Filter mix665k data based on new_ids | |
| new_data = [] | |
| for item in llava_v1_5_mix665k: | |
| all_conv = "" | |
| for cur_conversation in item["conversations"]: | |
| all_conv += cur_conversation["value"] | |
| if f'{item["id"]}_{all_conv}' in new_ids: | |
| new_data.append(item) | |
| import pdb | |
| pdb.set_trace() | |
| with open("/mnt/bn/vl-research/workspace/boli01/zzzprojects/LLaVA/playground/data/mixtral_instruct_135K_of_158K_V1.5.json") as f: | |
| new_mixtral_instruct = json.load(f) | |
| # mixtral_instruct_50K_of_80K_V1.json@ | |
| # print(len(new_data)) | |
| # for _ in new_mixtral_instruct: | |
| # # import pdb; pdb.set_trace() | |
| # if "coco" not in _["image"]: | |
| # _["image"] = f"coco/train2017/{_['image']}" | |
| # new_data.append(_) | |
| # print(len(instruct_150k_ids)) | |
| print(len(new_data)) | |
| # for _ in tqdm(new_data): | |
| # if "image" in _: | |
| # if "000000442654" in _["image"]: | |
| # all_conv = "" | |
| # for cur_conversation in _["conversations"]: | |
| # all_conv += cur_conversation["value"] | |
| # # if not os.path.exists(f'/mnt/bn/vl-research/workspace/boli01/data/playground/data/{_["image"]}'): | |
| # import pdb; pdb.set_trace() | |
| # Write new_data to a new JSON file | |
| with open("/mnt/bn/vl-research/workspace/boli01/zzzprojects/LLaVA/playground/data/llava_v1_5_mix665k_minus_llava_instruct_150k_minus_sharegpt_plus_mixtral_instruct_135K_of_158K_V1.5.json", "w") as f: | |
| json.dump(new_data, f) | |