yolo最新选择

2026-08-28 14:57:56 +08:00
parent 70aa072164
commit 231937afba
27 changed files with 418 additions and 29 deletions
@@ -0,0 +1,108 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""Run from MaixVision on PC to inspect the box's live 20/40 YOLO output."""
+
+import os
+
+from maix import app, camera, display, image, nn, time
+
+
+# This file is sent to /tmp/maixpy_run by MaixVision. Keep the model path
+# absolute so the script uses the model already installed on the box.
+MODEL_PATH = "/maixapp/apps/t11/model_317181.mud"
+CAMERA_WIDTH = 640
+CAMERA_HEIGHT = 480
+CONF_TH = 0.65
+IOU_TH = 0.45
+
+
+def _flatten_objects(raw):
+    if raw is None:
+        return []
+    if isinstance(raw, (list, tuple)):
+        result = []
+        for item in raw:
+            if isinstance(item, (list, tuple)):
+                result.extend(_flatten_objects(item))
+            else:
+                result.append(item)
+        return result
+    return [raw]
+
+
+def main():
+    if not os.path.isfile(MODEL_PATH):
+        raise FileNotFoundError("model not found on box: " + MODEL_PATH)
+
+    detector = nn.YOLOv5(model=MODEL_PATH, dual_buff=False)
+    cam = camera.Camera(CAMERA_WIDTH, CAMERA_HEIGHT)
+    disp = display.Display()
+
+    labels = tuple(str(label) for label in detector.labels)
+    print("[YOLO] model:", MODEL_PATH)
+    print("[YOLO] labels:", labels)
+    print("[YOLO] conf=%.2f iou=%.2f" % (CONF_TH, IOU_TH))
+
+    fps = 0.0
+    frame_count = 0
+    last_log_ms = time.ticks_ms()
+
+    while not app.need_exit():
+        loop_start_ms = time.ticks_ms()
+        img = cam.read()
+
+        detect_start_ms = time.ticks_ms()
+        raw = detector.detect(img, conf_th=CONF_TH, iou_th=IOU_TH)
+        detect_ms = max(0, time.ticks_diff(time.ticks_ms(), detect_start_ms))
+        objects = _flatten_objects(raw)
+
+        candidates = []
+        for obj in objects:
+            class_id = int(obj.class_id)
+            score = float(obj.score)
+            label = labels[class_id] if 0 <= class_id < len(labels) else "unknown"
+            color = image.COLOR_GREEN if label in ("20", "40") else image.COLOR_RED
+
+            img.draw_rect(obj.x, obj.y, obj.w, obj.h, color=color)
+            img.draw_string(
+                obj.x,
+                max(0, obj.y - 16),
+                "%scm %.2f" % (label, score),
+                color=color,
+            )
+            if label in ("20", "40"):
+                candidates.append((score, label))
+
+        loop_ms = max(1, time.ticks_diff(time.ticks_ms(), loop_start_ms))
+        instant_fps = 1000.0 / float(loop_ms)
+        fps = instant_fps if frame_count == 0 else fps * 0.9 + instant_fps * 0.1
+
+        if candidates:
+            best_score, best_label = max(candidates, key=lambda item: item[0])
+            status = "TARGET %scm %.2f" % (best_label, best_score)
+            status_color = image.COLOR_GREEN
+        else:
+            status = "TARGET UNKNOWN"
+            status_color = image.COLOR_RED
+
+        img.draw_string(5, 5, status, color=status_color)
+        img.draw_string(
+            5,
+            25,
+            "infer=%dms fps=%.1f boxes=%d" % (detect_ms, fps, len(objects)),
+            color=image.COLOR_YELLOW,
+        )
+        disp.show(img)
+
+        frame_count += 1
+        now_ms = time.ticks_ms()
+        if time.ticks_diff(now_ms, last_log_ms) >= 1000:
+            print(
+                "[YOLO] %s infer=%dms fps=%.1f boxes=%d"
+                % (status, detect_ms, fps, len(objects))
+            )
+            last_log_ms = now_ms
+
+
+if __name__ == "__main__":
+    main()