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fix: use do_sample_frames=False instead of video_kwargs fps list

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The Qwen3.5 processor expects fps as a scalar, not a list, so passing
video_kwargs with fps=[...] fails validation. Since process_vision_info
already handles frame sampling, we only need do_sample_frames=False to
tell the processor to use the pre-sampled frames as-is.

Made-with: Cursor
This commit is contained in:
Pepijn
2026-03-30 16:55:46 +02:00
parent e40985b013
commit 002a9dd0b9
1 changed files with 12 additions and 30 deletions
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src/lerobot/data_processing/data_annotations/vlm_annotations.py
+12 -30
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@@ -159,14 +159,12 @@ class Qwen2VL(BaseVLM):
]
text = self.processor.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
image_inputs, video_inputs, video_kwargs = self.process_vision_info(
messages, return_video_kwargs=True
)
image_inputs, video_inputs = self.process_vision_info(messages)
inputs = self.processor(
text=[text],
images=image_inputs,
videos=video_inputs,
**video_kwargs,
do_sample_frames=False,
padding=True,
return_tensors="pt",
).to(self.device)
@@ -213,23 +211,19 @@ class Qwen2VL(BaseVLM):
all_texts = []
all_image_inputs = []
all_video_inputs = []
all_video_kwargs: dict = {"do_sample_frames": False, "fps": []}
for messages in all_messages:
text = self.processor.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
image_inputs, video_inputs, video_kwargs = self.process_vision_info(
messages, return_video_kwargs=True
)
image_inputs, video_inputs = self.process_vision_info(messages)
all_texts.append(text)
all_image_inputs.extend(image_inputs or [])
all_video_inputs.extend(video_inputs or [])
all_video_kwargs["fps"].extend(video_kwargs.get("fps", []))
inputs = self.processor(
text=all_texts,
images=all_image_inputs if all_image_inputs else None,
videos=all_video_inputs if all_video_inputs else None,
**all_video_kwargs,
do_sample_frames=False,
padding=True,
return_tensors="pt",
).to(self.device)
@@ -338,14 +332,12 @@ class Qwen3VL(BaseVLM):
]
text = self.processor.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
image_inputs, video_inputs, video_kwargs = self.process_vision_info(
messages, return_video_kwargs=True
)
image_inputs, video_inputs = self.process_vision_info(messages)
inputs = self.processor(
text=[text],
images=image_inputs,
videos=video_inputs,
**video_kwargs,
do_sample_frames=False,
padding=True,
return_tensors="pt",
).to(self.device)
@@ -391,23 +383,19 @@ class Qwen3VL(BaseVLM):
all_texts = []
all_image_inputs = []
all_video_inputs = []
all_video_kwargs: dict = {"do_sample_frames": False, "fps": []}
for messages in all_messages:
text = self.processor.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
image_inputs, video_inputs, video_kwargs = self.process_vision_info(
messages, return_video_kwargs=True
)
image_inputs, video_inputs = self.process_vision_info(messages)
all_texts.append(text)
all_image_inputs.extend(image_inputs or [])
all_video_inputs.extend(video_inputs or [])
all_video_kwargs["fps"].extend(video_kwargs.get("fps", []))
inputs = self.processor(
text=all_texts,
images=all_image_inputs if all_image_inputs else None,
videos=all_video_inputs if all_video_inputs else None,
**all_video_kwargs,
do_sample_frames=False,
padding=True,
return_tensors="pt",
).to(self.device)
@@ -510,14 +498,12 @@ class Qwen35VL(BaseVLM):
text = self.processor.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True, enable_thinking=False
)
image_inputs, video_inputs, video_kwargs = self.process_vision_info(
messages, return_video_kwargs=True
)
image_inputs, video_inputs = self.process_vision_info(messages)
inputs = self.processor(
text=[text],
images=image_inputs,
videos=video_inputs,
**video_kwargs,
do_sample_frames=False,
padding=True,
return_tensors="pt",
).to(self.device)
@@ -562,25 +548,21 @@ class Qwen35VL(BaseVLM):
all_texts = []
all_image_inputs = []
all_video_inputs = []
all_video_kwargs: dict = {"do_sample_frames": False, "fps": []}
for messages in all_messages:
text = self.processor.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True, enable_thinking=False
)
image_inputs, video_inputs, video_kwargs = self.process_vision_info(
messages, return_video_kwargs=True
)
image_inputs, video_inputs = self.process_vision_info(messages)
all_texts.append(text)
all_image_inputs.extend(image_inputs or [])
all_video_inputs.extend(video_inputs or [])
all_video_kwargs["fps"].extend(video_kwargs.get("fps", []))
inputs = self.processor(
text=all_texts,
images=all_image_inputs if all_image_inputs else None,
videos=all_video_inputs if all_video_inputs else None,
**all_video_kwargs,
do_sample_frames=False,
padding=True,
return_tensors="pt",
).to(self.device)