5f84f4f2a7
app.py becomes the recognition server: /v1 REST (health, catalog + template images, samples, recognize, classify, inspect, stock) plus /v1/stream over WebSocket, with token auth, size limits, one consistent error shape, and the legacy /api/sessions routes kept but now backed by the real engine instead of the fake adapter. Default bind is 127.0.0.1; LAN and TLS are opt-in. stream_client.py is the reference non-browser client (camera, video file, or a pan across a still) and prints results/s, RTT, detect time and label stability. Live quality work driven by measurements: - Labels are remembered per place: a fresh track covering a recently recognized product inherits the label instead of queueing for classification again. On a continuous pan this raised recognized products in view from 9/66 to 17-21/66 and cut time-to-first-label to ~1.6 s. - Classification priority is newest-first, because sorting by area spends the budget on products that are already leaving the frame. - Per-session classification concurrency raised to 12. hybrid_fast (ORB shortlist then hybrid) is implemented but NOT the default: it is 3.4x faster (13 ms vs 44 ms p50) yet agreed with hybrid on only 47% of accepted crops across 553 crops, far below the 98% adoption rule. It stays available for experiments; the numbers are in the commit and the benchmark. Co-Authored-By: Devin <158243242+devin-ai-integration[bot]@users.noreply.github.com>
283 lines
12 KiB
Python
283 lines
12 KiB
Python
"""
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Reference live client for the Dorayaki recognition server.
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Streams frames over WebSocket /v1/stream and prints what the server sees. This
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is the documented example for capture sources that are not a browser: a cart
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camera, a wearable camera, a rail camera, a robot.
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Usage (from recognization/):
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.venv/bin/python code/stream_client.py --source image.jpg --pan 12 --seconds 20
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.venv/bin/python code/stream_client.py --source 0 # webcam index
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.venv/bin/python code/stream_client.py --source clip.mp4 --seconds 30
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.venv/bin/python code/stream_client.py --url ws://host:8080/v1/stream --token SECRET
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Frame protocol: 4-byte big-endian frame id + JPEG bytes.
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"""
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from __future__ import annotations
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import argparse
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import json
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import os
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import statistics
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import sys
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import time
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from typing import Any, Dict, List, Optional
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current_dir = os.path.dirname(os.path.abspath(__file__))
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project_root = os.path.dirname(current_dir)
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if os.path.exists(os.path.join(project_root, "stock")):
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os.chdir(project_root)
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if current_dir not in sys.path:
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sys.path.insert(0, current_dir)
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import cv2 # noqa: E402
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from websockets.sync.client import connect # noqa: E402
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def percentile(values: List[float], pct: float) -> float:
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if not values:
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return 0.0
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ordered = sorted(values)
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index = min(len(ordered) - 1, max(0, int(round((pct / 100.0) * (len(ordered) - 1)))))
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return ordered[index]
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class FrameSource:
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"""Yields BGR frames from a camera, a video file, or a still image pan."""
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def __init__(self, source: str, *, width: int, pan_step: int, pan_width: int = 1280):
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self.source = source
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self.width = width
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self.pan_step = pan_step
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self.pan_width = pan_width
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self.capture: Optional[cv2.VideoCapture] = None
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self.image = None
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self.pan_x = 0
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self.pan_direction = 1
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if source.isdigit():
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self.capture = cv2.VideoCapture(int(source))
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elif os.path.isfile(source) and source.lower().endswith((".mp4", ".mov", ".avi", ".mkv", ".webm")):
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self.capture = cv2.VideoCapture(source)
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else:
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self.image = cv2.imread(source)
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if self.image is None:
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raise SystemExit(f"cannot read source {source}")
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def frame(self, index: int):
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if self.image is not None:
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height, width = self.image.shape[:2]
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window_w = min(self.pan_width, width)
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window_h = min(int(window_w * 9 / 16), height)
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max_x = max(0, width - window_w)
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x = min(self.pan_x, max_x)
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y = max(0, (height - window_h) // 2)
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window = self.image[y:y + window_h, x:x + window_w]
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self.pan_x += self.pan_direction * self.pan_step
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if self.pan_x >= max_x or self.pan_x <= 0:
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self.pan_direction *= -1
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return window
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if self.capture is not None:
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ok, frame = self.capture.read()
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if not ok: # loop video files
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self.capture.set(cv2.CAP_PROP_POS_FRAMES, 0)
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ok, frame = self.capture.read()
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if not ok:
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return None
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return frame
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return None
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def release(self) -> None:
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if self.capture is not None:
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self.capture.release()
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def encode(frame, width: int, quality: int) -> bytes:
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height, current_width = frame.shape[:2]
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if width and current_width > width:
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scale = width / float(current_width)
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frame = cv2.resize(frame, (int(width), int(round(height * scale))))
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ok, buffer = cv2.imencode(".jpg", frame, [cv2.IMWRITE_JPEG_QUALITY, quality])
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if not ok:
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raise RuntimeError("JPEG encode failed")
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return buffer.tobytes()
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def main() -> None:
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parser = argparse.ArgumentParser(description="Dorayaki live stream client")
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parser.add_argument("--url", default="ws://127.0.0.1:8080/v1/stream")
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parser.add_argument("--token", default=os.environ.get("DORAYAKI_API_TOKEN"))
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parser.add_argument("--source", default="image.jpg", help="camera index, video path, or image path")
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parser.add_argument("--pan", type=int, default=12, help="pixels per frame when panning a still image")
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parser.add_argument("--seconds", type=float, default=20.0)
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parser.add_argument("--width", type=int, default=1280, help="send width")
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parser.add_argument("--quality", type=int, default=75)
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parser.add_argument("--max-inflight", type=int, default=1)
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parser.add_argument("--pace", choices=["send", "result"], default="send",
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help="'send': keep the socket busy (frames drop server-side); "
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"'result': send the next frame only after a result, so the "
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"pan stays continuous (the mode to use for stability checks)")
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parser.add_argument("--method", default=None, help="surf | orb | brisk | hybrid")
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parser.add_argument("--json", action="store_true", help="print a JSON summary instead of the table")
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parser.add_argument("--quiet", action="store_true", help="only print the final summary")
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args = parser.parse_args()
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url = args.url
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if args.token and "token=" not in url:
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url = f"{url}{'&' if '?' in url else '?'}token={args.token}"
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source = FrameSource(args.source, width=args.width, pan_step=args.pan)
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rtts: List[float] = []
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detect_times: List[float] = []
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frames_sent = 0
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results = 0
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drops = 0
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first_label: Dict[int, float] = {}
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label_latencies: List[float] = []
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labels: Dict[int, str] = {}
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label_changes = 0
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unexplained_changes = 0
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relabel_seen: Dict[int, int] = {}
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restart_seen: Dict[int, int] = {}
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inherited_seen: Dict[int, bool] = {}
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seen_tracks: set = set()
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last_summary: Dict[str, Any] = {}
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started = time.perf_counter()
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in_flight: Dict[int, float] = {}
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pending_frame: Optional[int] = None
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with connect(url, max_size=8 * 1024 * 1024) as socket:
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hello = json.loads(socket.recv(timeout=10))
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if hello.get("type") != "hello":
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raise SystemExit(f"unexpected first message: {hello}")
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if not args.quiet:
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print(f"hello: session {hello['session_id']} model {hello['model']['version']} "
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f"device {hello['model']['device']} config {hello['config']}")
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if args.method:
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socket.send(json.dumps({"type": "config", "method": args.method}))
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ack = json.loads(socket.recv(timeout=10))
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if not args.quiet:
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print(f"config ack: {ack.get('config')}")
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def consume(message: Dict[str, Any]) -> None:
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"""Fold one result into the running metrics."""
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nonlocal results, last_summary, label_changes, unexplained_changes
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if message.get("type") != "result":
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if not args.quiet:
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print(f"server message: {message}")
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return
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received_at = time.perf_counter()
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sent_at = in_flight.pop(message["frame_id"], None)
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if sent_at is not None:
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rtts.append((received_at - sent_at) * 1000.0)
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detect_times.append(message["timing_ms"]["detect"])
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results += 1
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last_summary = message["summary"]
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now = time.perf_counter()
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for track in message["tracks"]:
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track_id = track["track_id"]
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seen_tracks.add(track_id)
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identity = track["identity"]
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if identity["state"] != "recognized":
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continue
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sku = identity["sku_id"]
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relabels = track.get("relabels", 0)
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restarts = track.get("restarts", 0)
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if restarts > restart_seen.get(track_id, 0):
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# The id was restarted: earlier labels describe another object.
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labels.pop(track_id, None)
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first_label.pop(track_id, None)
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inherited = bool(track.get("inherited"))
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if track_id not in first_label:
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first_label[track_id] = now
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if not inherited:
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label_latencies.append((now - started) * 1000.0)
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elif labels.get(track_id) != sku:
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# Only a measured-to-measured change on the same object is a
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# label change; inherited labels describe the same product
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# under a new track id.
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if not inherited and not inherited_seen.get(track_id):
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label_changes += 1
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if relabels <= relabel_seen.get(track_id, 0):
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unexplained_changes += 1
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labels[track_id] = sku
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inherited_seen[track_id] = inherited
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relabel_seen[track_id] = relabels
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restart_seen[track_id] = restarts
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if not args.quiet and results % 10 == 0:
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print(f"f{message['seq']:04d} tracks={len(message['tracks']):3d} "
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f"recognized={last_summary['recognized']:3d} "
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f"unconfirmed={last_summary.get('unconfirmed', 0):3d} "
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f"detect={message['timing_ms']['detect']:5.1f}ms "
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f"rtt={rtts[-1]:6.1f}ms fps={results / (now - started):5.2f}")
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frame_id = 0
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index = 0
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while time.perf_counter() - started < args.seconds:
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frame = source.frame(index)
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if frame is None:
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break
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index += 1
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frame_id = (frame_id + 1) & 0xFFFFFFFF
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payload = encode(frame, args.width, args.quality)
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if len(in_flight) >= args.max_inflight:
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if pending_frame is not None:
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drops += 1
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pending_frame = frame_id
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socket.send(frame_id.to_bytes(4, "big") + payload, text=False)
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frames_sent += 1
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else:
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socket.send(frame_id.to_bytes(4, "big") + payload, text=False)
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frames_sent += 1
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in_flight[frame_id] = time.perf_counter()
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if args.pace == "result":
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# One frame in flight: the next frame is captured only after this
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# one was answered, so the pan stays continuous.
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while in_flight:
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try:
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consume(json.loads(socket.recv(timeout=5)))
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except TimeoutError:
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print("timeout waiting for a result")
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break
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continue
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try:
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consume(json.loads(socket.recv(timeout=5)))
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except TimeoutError:
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print("timeout waiting for a result")
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break
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source.release()
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elapsed = time.perf_counter() - started
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summary = {
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"seconds": round(elapsed, 1),
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"frames_sent": frames_sent,
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"results": results,
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"results_per_s": round(results / elapsed, 2) if elapsed else 0,
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"frames_dropped_by_client": drops,
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"rtt_ms_p50": round(statistics.median(rtts), 1) if rtts else None,
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"rtt_ms_p95": round(percentile(rtts, 95), 1) if rtts else None,
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"server_detect_ms_p50": round(statistics.median(detect_times), 1) if detect_times else None,
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"server_detect_ms_p95": round(percentile(detect_times, 95), 1) if detect_times else None,
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"tracks_seen": len(seen_tracks),
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"tracks_labelled": len(labels),
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"label_changes": label_changes,
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"unexplained_label_changes": unexplained_changes,
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"first_label_ms_p50": round(statistics.median(label_latencies), 0) if label_latencies else None,
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"final_summary": last_summary,
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}
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if args.json:
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print(json.dumps(summary, indent=2))
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else:
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print("\n--- stream summary ---")
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for key, value in summary.items():
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if key != "final_summary":
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print(f"{key:24s} {value}")
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print(f"{'final_summary':24s} {json.dumps(last_summary, ensure_ascii=False)}")
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if results == 0:
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sys.exit(1)
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if __name__ == "__main__":
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main()
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