Video Inference - TypeError: process_vision_info() got an unexpected keyword argument 'return_video_kwargs'
#2
by hmanju - opened
messages = [
{
"role": "user",
"content": [
{
"type": "video",
"video": "file:///path/to/video1.mp4", #added local file path for a video here
"max_pixels": 360 * 420,
"fps": 1.0,
},
{"type": "text", "text": "Describe this video."},
],
}
]
#In Qwen 2.5 VL, frame rate information is also input into the model to align with absolute time.
# Preparation for inference
text = processor.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
image_inputs, video_inputs, video_kwargs = process_vision_info(messages, return_video_kwargs=True)
inputs = processor(
text=[text],
images=image_inputs,
videos=video_inputs,
fps=fps,
padding=True,
return_tensors="pt",
**video_kwargs,
)
inputs = inputs.to("cuda")
# Inference
generated_ids = model.generate(**inputs, max_new_tokens=128)
generated_ids_trimmed = [
out_ids[len(in_ids) :] for in_ids, out_ids in zip(inputs.input_ids, generated_ids)
]
output_text = processor.batch_decode(
generated_ids_trimmed, skip_special_tokens=True, clean_up_tokenization_spaces=False
)
print(output_text)
TypeError Traceback (most recent call last)
/tmp/ipykernel_213370/404839378.py in <module>
34 messages, tokenize=False, add_generation_prompt=True
35 )
---> 36 image_inputs, video_inputs, video_kwargs = process_vision_info(messages, return_video_kwargs=True)
37 inputs = processor(
38 text=[text],
TypeError: process_vision_info() got an unexpected keyword argument 'return_video_kwargs'
Same here with the video example, but I had success just reusing the image example (which includes video params already) and changing the content from image to video.
something like
messages = [
{
"role": "user",
"content": [
{"type": "video", "video": "file:///path/to/video1.mp4"}
{"type": "text", "text": "Describe this video."},
]
}
]
text = processor.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
image_inputs, video_inputs = process_vision_info(messages)
inputs = processor(
text=[text],
images=image_inputs,
videos=video_inputs,
padding=True,
return_tensors="pt",
)
inputs = inputs.to("cuda")
# etc
There's also far more detailed "cookbooks" on their github, including for video.
+1