MixEval-X Image / Video

lmms_eval/filters/extraction.py

@@ -1,7 +1,10 @@
+import os
 import re
 import sys
 import unicodedata
 
+import openai
+
 from lmms_eval.api.filter import Filter
 
 

lmms_eval/models/internvl2.py

@@ -139,8 +139,8 @@ def __init__(
         super().__init__()
 
         self.path = pretrained
-        self._model = AutoModel.from_pretrained(self.path, torch_dtype=torch.bfloat16, low_cpu_mem_usage=True, trust_remote_code=True).eval().cuda()
-        self._tokenizer = AutoTokenizer.from_pretrained(self.path, trust_remote_code=True)
+        self._model = AutoModel.from_pretrained(self.path, torch_dtype=torch.bfloat16, low_cpu_mem_usage=True, trust_remote_code=True, device_map=device_map).eval()
+        self._tokenizer = AutoTokenizer.from_pretrained(self.path, trust_remote_code=True, device_map=device_map)
 
         batch_size = int(batch_size)
         assert batch_size == 1, f"Batch size should be 1 for InternVL2, but got {batch_size}."

lmms_eval/models/llama_vision.py

@@ -15,6 +15,7 @@
 from lmms_eval.api.instance import Instance
 from lmms_eval.api.model import lmms
 from lmms_eval.api.registry import register_model
+from lmms_eval.models.model_utils.load_video import read_video_pyav_pil
 
 warnings.filterwarnings("ignore")
 
@@ -25,33 +26,19 @@
 
 @register_model("llama_vision")
 class LlamaVision(lmms):
-    """
-    Llava Model for Hugging Face Transformers: https://huggingface.co/docs/transformers/v4.39.3/en/model_doc/llava
-
-    Adapted from the InstructBLIP model in lmms_eval/models/instructblip.py
-
-    Example usage:
-
-    accelerate launch --num_processes=8 --main_process_port 12345 -m lmms_eval \
-        --model llava_hf \
-        --model_args pretrained=llava-hf/llava-1.5-7b-hf \
-        --tasks seedbench \
-        --batch_size 1 \
-        --output_path ./logs/ \
-        --log_samples
-    """
-
     def __init__(
         self,
         pretrained: str = "meta-llama/Llama-3.2-11B-Vision",
         revision: str = "main",
         device: str = "cuda",
         dtype: Optional[Union[str, torch.dtype]] = "auto",
         batch_size: int = 1,
-        trust_remote_code: Optional[bool] = False,
+        trust_remote_code: Optional[bool] = True,
         attn_implementation: Optional[str] = None,
         device_map: str = "",
         max_frames_num: Optional[int] = 32,
+        fps: Optional[int] = None,
+        max_image_size: Optional[int] = None,
         **kwargs,
     ) -> None:
         super().__init__()
@@ -68,7 +55,9 @@ def __init__(
         if isinstance(dtype, str) and dtype != "auto":
             dtype = getattr(torch, dtype)
 
+        self.fps = fps
         self.max_frames_num = max_frames_num
+        self.max_image_size = max_image_size
         self._model = MllamaForConditionalGeneration.from_pretrained(pretrained, revision=revision, torch_dtype=dtype, device_map=self.device_map, trust_remote_code=trust_remote_code, attn_implementation=attn_implementation)
         self.model.eval()
         self.processor = AutoProcessor.from_pretrained(pretrained)
@@ -193,9 +182,11 @@ def generate_until(self, requests: List[Instance]) -> List[str]:
 
             for visual in visuals:
                 if isinstance(visual, str):
-                    frames = self.load_video(visual, self.max_frames_num)
-                    frames = torch.from_numpy(frames).permute(0, 3, 1, 2)
-                    images.extend([to_pil_image(frame) for frame in frames])
+                    frames = read_video_pyav_pil(visual, num_frm=self.max_frames_num, fps=self.fps, max_image_size=self.max_image_size)
+                    images.extend(frames)
+                    # frames = self.load_video(visual, self.max_frames_num)
+                    # frames = torch.from_numpy(frames).permute(0, 3, 1, 2)
+                    # images.extend([to_pil_image(frame) for frame in frames])
                 elif isinstance(visual, PIL.Image.Image):
                     images.append(visual)
 

lmms_eval/models/llava_vid.py

@@ -90,7 +90,7 @@ def __init__(
         conv_template="vicuna_v1",
         use_cache=True,
         truncate_context=False,  # whether to truncate the context in generation, set it False for LLaVA-1.6
-        max_frames_num: int = 3,
+        max_frames_num: int = 20,
         video_fps: int = 1,
         mm_resampler_type: str = "spatial_pool",
         mm_spatial_pool_stride: int = 2,

lmms_eval/tasks/__init__.py

@@ -417,6 +417,8 @@ def _get_task_and_group(self, task_dir: str):
                             "yaml_path": yaml_path,
                         }
                     elif self._config_is_group(config):
+                        if f.endswith("mix_evals_image2text.yaml"):
+                            print(config)
                         # This is a group config
                         tasks_and_groups[config["group"]] = {
                             "type": "group",
@@ -477,6 +479,7 @@ def _get_task_and_group(self, task_dir: str):
                     else:
                         self.logger.debug(f"File {f} in {root} could not be loaded as a task or group")
 
+        print(tasks_and_groups["mix_evals_image2text"])
         return tasks_and_groups
 
 

lmms_eval/tasks/mix_evals/audio2text/mix_evals_audio2text.yaml

@@ -0,0 +1,3 @@
+group: mix_evals_audio2text
+task:
+- mix_evals_audio2_text_freeform

lmms_eval/tasks/mix_evals/image2text/_default_template_yaml

@@ -0,0 +1,13 @@
+dataset_path: MixEval/MixEval-X
+dataset_kwargs:
+  video: true # a bit confusing, but this is because the official uses path to store image data, so we need to load it as a video dataset
+  cache_dir: mix_evals_image2text
+lmms_eval_specific_kwargs:
+  default:
+    post_prompt: ""
+    pre_prompt: ""
+  gpt4v:
+    post_prompt: ""
+    pre_prompt: ""
+metadata:
+  version: 0

lmms_eval/tasks/mix_evals/image2text/mix_evals_image2text.yaml

@@ -0,0 +1,4 @@
+group: mix_evals_image2text
+task:
+- mix_evals_image2text_mc
+- mix_evals_image2text_freeform

lmms_eval/tasks/mix_evals/image2text/mix_evals_image2text_freeform.yaml

@@ -0,0 +1,17 @@
+task: "mix_evals_image2text_freeform"
+dataset_name: "image2text"
+test_split: free_form
+output_type: generate_until
+doc_to_visual: !function utils.mix_evals_image2text_doc_to_visual
+doc_to_text: !function utils.mix_evals_image2text_doc_to_text
+doc_to_target: "{{reference_answer}}"
+process_results: !function utils.mix_evals_image2text_process_results_freeform
+metric_list:
+  - metric: gpt_eval
+    aggregation: !function utils.mix_evals_image2text_gpt_eval
+    higher_is_better: true
+
+generation_kwargs:
+  max_new_tokens: 1024
+
+include: _default_template_yaml

lmms_eval/tasks/mix_evals/image2text/mix_evals_image2text_freeform_hard.yaml

@@ -0,0 +1,25 @@
+task: "mix_evals_image2text_freeform_hard"
+dataset_name: "image2text"
+test_split: free_form_hard
+output_type: generate_until
+doc_to_visual: !function utils.mix_evals_image2text_doc_to_visual
+doc_to_text: !function utils.mix_evals_image2text_doc_to_text
+doc_to_target: "{{reference_answer}}"
+process_results: !function utils.mix_evals_image2text_process_results_freeform
+metric_list:
+  - metric: gpt_eval
+    aggregation: !function utils.mix_evals_image2text_gpt_eval
+    higher_is_better: true
+
+generation_kwargs:
+  max_new_tokens: 1024
+
+include: _default_template_yaml
+
+lmms_eval_specific_kwargs:
+  default:
+    pre_prompt: "Please answer the following questions about the image."
+    post_prompt: ""
+  gpt4v:
+    pre_prompt: "Please answer the following questions about the image."
+    post_prompt: ""

lmms_eval/tasks/mix_evals/image2text/mix_evals_image2text_hard.yaml

@@ -0,0 +1,5 @@
+group: mix_evals_image2text_hard
+task:
+- mix_evals_image2text_mc_hard
+- mix_evals_image2text_freeform_hard
+# - mix_evals_image2text_openended

lmms_eval/tasks/mix_evals/image2text/mix_evals_image2text_mc.yaml

@@ -0,0 +1,23 @@
+include: _default_template_yaml
+task: "mix_evals_image2text_mc"
+dataset_name: "image2text"
+test_split: multiple_choice
+output_type: generate_until
+doc_to_visual: !function utils.mix_evals_image2text_doc_to_visual
+doc_to_text: !function utils.mix_evals_image2text_doc_to_text
+doc_to_target: "{{reference_answer}}"
+
+generation_kwargs:
+  max_new_tokens: 1024
+
+metric_list:
+  - metric: exact_match
+    aggregation: mean
+    higher_is_better: true
+    ignore_case: true
+    ignore_punctuation: true
+
+filter_list:
+  - name: "flexible-extract"
+    filter:
+      - function: !function utils.GPTMultiChoiceFilter

lmms_eval/tasks/mix_evals/image2text/mix_evals_image2text_mc_hard.yaml

@@ -0,0 +1,23 @@
+include: _default_template_yaml
+task: "mix_evals_image2text_mc_hard"
+dataset_name: "image2text"
+test_split: multiple_choice_hard
+output_type: generate_until
+doc_to_visual: !function utils.mix_evals_image2text_doc_to_visual
+doc_to_text: !function utils.mix_evals_image2text_doc_to_text
+doc_to_target: "{{reference_answer}}"
+
+generation_kwargs:
+  max_new_tokens: 1024
+
+metric_list:
+  - metric: exact_match
+    aggregation: mean
+    higher_is_better: true
+    ignore_case: true
+    ignore_punctuation: true
+
+filter_list:
+  - name: "flexible-extract"
+    filter:
+      - function: !function utils.GPTMultiChoiceFilter