phase cv 0

This commit is contained in:
2026-03-26 22:22:35 -03:00
parent beb0416280
commit 65814b5b9e
46 changed files with 2962 additions and 268 deletions

View File

@@ -26,6 +26,7 @@ class OverrideProfile:
{
"frame_extraction": {"fps": 1.0},
"scene_filter": {"hamming_threshold": 12},
"region_analysis": {"edge_canny_low": 30, "edge_canny_high": 120},
"detection": {"confidence_threshold": 0.5},
"ocr": {"languages": ["en", "es"], "min_confidence": 0.3},
"resolver": {"fuzzy_threshold": 60},
@@ -52,6 +53,9 @@ class OverrideProfile:
def scene_filter_config(self):
return self._patch(self._base.scene_filter_config(), "scene_filter")
def region_analysis_config(self):
return self._patch(self._base.region_analysis_config(), "region_analysis")
def detection_config(self):
return self._patch(self._base.detection_config(), "detection")
@@ -130,3 +134,137 @@ def replay_from(
emit.clear_run_context()
return result
def replay_single_stage(
job_id: str,
stage: str,
frame_refs: list[int] | None = None,
config_overrides: dict | None = None,
debug: bool = False,
) -> dict:
"""
Replay a single stage on specific frames (or all frames from checkpoint).
Fast path for interactive parameter tuning — runs only the target stage
function, not the full pipeline tail. Returns the stage output directly.
When debug=True and stage is detect_edges, returns additional overlay
data (Canny edges, Hough lines) for visual feedback in the editor.
For detect_edges: returns {"edge_regions_by_frame": {seq: [box, ...]}}
With debug=True, also returns {"debug": {seq: {edge_overlay_b64, lines_overlay_b64, ...}}}
"""
if stage not in NODES:
raise ValueError(f"Unknown stage: {stage!r}. Options: {NODES}")
stage_idx = NODES.index(stage)
if stage_idx == 0:
raise ValueError("Cannot replay the first stage — just run the full pipeline")
previous_stage = NODES[stage_idx - 1]
available = list_checkpoints(job_id)
if previous_stage not in available:
raise ValueError(
f"No checkpoint for stage {previous_stage!r} (job {job_id}). "
f"Available: {available}"
)
logger.info("Single-stage replay: job %s, stage %s (loading checkpoint: %s, debug=%s)",
job_id, stage, previous_stage, debug)
state = load_checkpoint(job_id, previous_stage)
# Build profile with overrides
from detect.profiles import get_profile
profile = get_profile(state.get("profile_name", "soccer_broadcast"))
if config_overrides:
profile = OverrideProfile(profile, config_overrides)
# Run the stage function directly (not through the graph)
if stage == "detect_edges":
return _replay_detect_edges(state, profile, frame_refs, job_id, debug)
else:
raise ValueError(
f"Single-stage replay not yet implemented for {stage!r}. "
f"Use replay_from() for full pipeline replay."
)
def _replay_detect_edges(
state: dict,
profile,
frame_refs: list[int] | None,
job_id: str,
debug: bool,
) -> dict:
"""Run edge detection on checkpoint frames, optionally with debug overlays."""
import os
from detect.stages.edge_detector import detect_edge_regions
config = profile.region_analysis_config()
frames = state.get("filtered_frames", [])
if frame_refs:
ref_set = set(frame_refs)
frames = [f for f in frames if f.sequence in ref_set]
inference_url = os.environ.get("INFERENCE_URL")
# Normal run — always needed for the boxes
result = detect_edge_regions(
frames=frames,
config=config,
inference_url=inference_url,
job_id=job_id,
)
output = {"edge_regions_by_frame": result}
# Debug overlays — call debug endpoint (remote) or local debug function
if debug and frames:
debug_data = {}
if inference_url:
from detect.inference import InferenceClient
client = InferenceClient(base_url=inference_url, job_id=job_id)
for frame in frames:
dr = client.detect_edges_debug(
image=frame.image,
edge_canny_low=config.edge_canny_low,
edge_canny_high=config.edge_canny_high,
edge_hough_threshold=config.edge_hough_threshold,
edge_hough_min_length=config.edge_hough_min_length,
edge_hough_max_gap=config.edge_hough_max_gap,
edge_pair_max_distance=config.edge_pair_max_distance,
edge_pair_min_distance=config.edge_pair_min_distance,
)
debug_data[frame.sequence] = {
"edge_overlay_b64": dr.edge_overlay_b64,
"lines_overlay_b64": dr.lines_overlay_b64,
"horizontal_count": dr.horizontal_count,
"pair_count": dr.pair_count,
}
else:
# Local mode — import GPU module directly
from detect.stages.edge_detector import _load_cv_edges
edges_mod = _load_cv_edges()
for frame in frames:
dr = edges_mod.detect_edges_debug(
frame.image,
canny_low=config.edge_canny_low,
canny_high=config.edge_canny_high,
hough_threshold=config.edge_hough_threshold,
hough_min_length=config.edge_hough_min_length,
hough_max_gap=config.edge_hough_max_gap,
pair_max_distance=config.edge_pair_max_distance,
pair_min_distance=config.edge_pair_min_distance,
)
debug_data[frame.sequence] = {
"edge_overlay_b64": dr["edge_overlay_b64"],
"lines_overlay_b64": dr["lines_overlay_b64"],
"horizontal_count": dr["horizontal_count"],
"pair_count": dr["pair_count"],
}
output["debug"] = debug_data
return output