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trap
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Text formatting

This commit is contained in:
Ruben van de Ven 2024-05-02 20:31:52 +02:00
parent dc7d95bbce
commit 89076650c4
1 changed files with 4 additions and 4 deletions
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8
trap/renderer.py
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@ -195,7 +195,7 @@ def decorate_frame(frame: Frame, prediction_frame: Frame, first_time: float, con
cv2.rectangle(img, (0,0), (img.shape[1],25), (0,0,0), -1)
if not prediction_frame:
cv2.putText(img, f"Waiting for prediction...", (20,20), cv2.FONT_HERSHEY_PLAIN, 1, (255,255,0), 1)
cv2.putText(img, f"Waiting for prediction...", (500,17), cv2.FONT_HERSHEY_PLAIN, 1, (255,255,0), 1)
# continue
else:
inv_H = np.linalg.pinv(prediction_frame.H)
@ -264,9 +264,9 @@ def decorate_frame(frame: Frame, prediction_frame: Frame, first_time: float, con
cv2.putText(img, f"{prediction_frame.index - frame.index}", (90,17), cv2.FONT_HERSHEY_PLAIN, 1, info_color, 1)
cv2.putText(img, f"{prediction_frame.time - time.time():.2f}s", (200,17), cv2.FONT_HERSHEY_PLAIN, 1, info_color, 1)
cv2.putText(img, f"{len(prediction_frame.tracks)} tracks", (500,17), cv2.FONT_HERSHEY_PLAIN, 1, base_color, 1)
cv2.putText(img, f"h: {np.average([len(t.history or []) for t in prediction_frame.tracks.values()])}", (580,17), cv2.FONT_HERSHEY_PLAIN, 1, info_color, 1)
cv2.putText(img, f"ph: {np.average([len(t.predictor_history or []) for t in prediction_frame.tracks.values()])}", (660,17), cv2.FONT_HERSHEY_PLAIN, 1, info_color, 1)
cv2.putText(img, f"p: {np.average([len(t.predictions or []) for t in prediction_frame.tracks.values()])}", (740,17), cv2.FONT_HERSHEY_PLAIN, 1, info_color, 1)
cv2.putText(img, f"h: {np.average([len(t.history or []) for t in prediction_frame.tracks.values()]):.2f}", (580,17), cv2.FONT_HERSHEY_PLAIN, 1, info_color, 1)
cv2.putText(img, f"ph: {np.average([len(t.predictor_history or []) for t in prediction_frame.tracks.values()]):.2f}", (660,17), cv2.FONT_HERSHEY_PLAIN, 1, info_color, 1)
cv2.putText(img, f"p: {np.average([len(t.predictions or []) for t in prediction_frame.tracks.values()]):.2f}", (740,17), cv2.FONT_HERSHEY_PLAIN, 1, info_color, 1)
options = []
for option in ['prediction_horizon','num_samples','full_dist','gmm_mode','z_mode', 'model_dir']: