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Limit based on frames per second

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This commit is contained in:
Nicolas Mowen 2026-04-25 15:09:39 -06:00
parent ceaf0e386f
commit 4509f2c76c
1 changed files with 17 additions and 7 deletions
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24
frigate/data_processing/post/review_descriptions.py
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@ -40,6 +40,7 @@ logger = logging.getLogger(__name__)
RECORDING_BUFFER_EXTENSION_PERCENT = 0.10 RECORDING_BUFFER_EXTENSION_PERCENT = 0.10
MIN_RECORDING_DURATION = 10 MIN_RECORDING_DURATION = 10
MAX_IMAGE_TOKENS = 24000 MAX_IMAGE_TOKENS = 24000
MAX_FRAMES_PER_SECOND = 2
class ReviewDescriptionProcessor(PostProcessorApi): class ReviewDescriptionProcessor(PostProcessorApi):
@ -61,17 +62,22 @@ class ReviewDescriptionProcessor(PostProcessorApi):
def calculate_frame_count( def calculate_frame_count(
self, self,
camera: str, camera: str,
duration: float,
image_source: ImageSourceEnum = ImageSourceEnum.preview, image_source: ImageSourceEnum = ImageSourceEnum.preview,
height: int = 480, height: int = 480,
) -> int: ) -> int:
"""Calculate optimal number of frames based on context size, image source, and resolution. """Calculate optimal number of frames based on event duration, context size,
image source, and resolution.
Per-image token cost is asked of the GenAI provider so providers that know Per-image token cost is asked of the GenAI provider so providers that know
their model's true cost (e.g. llama.cpp can probe the loaded mmproj) can their model's true cost (e.g. llama.cpp can probe the loaded mmproj) can
diverge from the default ~1-token-per-1250-pixels heuristic. The frame diverge from the default ~1-token-per-1250-pixels heuristic. The frame
budget is bounded by both the remaining context window and a fixed budget is bounded by:
MAX_IMAGE_TOKENS ceiling so cheap-per-image models get more frames while - remaining context window after prompt + response reservations
expensive-per-image models stay reined in. - a fixed MAX_IMAGE_TOKENS ceiling
- MAX_FRAMES_PER_SECOND x duration, to avoid drowning short events in
near-duplicate frames where the model latches onto the redundant middle
and skips the start/end action
""" """
client = self.genai_manager.description_client client = self.genai_manager.description_client
@ -114,7 +120,9 @@ class ReviewDescriptionProcessor(PostProcessorApi):
response_tokens = 300 response_tokens = 300
context_budget = context_size - prompt_tokens - response_tokens context_budget = context_size - prompt_tokens - response_tokens
image_token_budget = min(context_budget, MAX_IMAGE_TOKENS) image_token_budget = min(context_budget, MAX_IMAGE_TOKENS)
max_frames = int(image_token_budget / tokens_per_image) max_frames_by_tokens = int(image_token_budget / tokens_per_image)
max_frames_by_duration = int(duration * MAX_FRAMES_PER_SECOND)
max_frames = min(max_frames_by_tokens, max_frames_by_duration)
return max(max_frames, 3) return max(max_frames, 3)
def process_data( def process_data(
@ -379,7 +387,9 @@ class ReviewDescriptionProcessor(PostProcessorApi):
all_frames.append(os.path.join(preview_dir, file)) all_frames.append(os.path.join(preview_dir, file))
frame_count = len(all_frames) frame_count = len(all_frames)
desired_frame_count = self.calculate_frame_count(camera) desired_frame_count = self.calculate_frame_count(
camera, duration=end_time - start_time
)
if frame_count <= desired_frame_count: if frame_count <= desired_frame_count:
return all_frames return all_frames
@ -403,7 +413,7 @@ class ReviewDescriptionProcessor(PostProcessorApi):
"""Get frames from recordings at specified timestamps.""" """Get frames from recordings at specified timestamps."""
duration = end_time - start_time duration = end_time - start_time
desired_frame_count = self.calculate_frame_count( desired_frame_count = self.calculate_frame_count(
camera, ImageSourceEnum.recordings, height camera, duration, ImageSourceEnum.recordings, height
) )
# Calculate evenly spaced timestamps throughout the duration # Calculate evenly spaced timestamps throughout the duration