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Add previous trajectories to vis_result function and check if vis/nba/ directory exists #8

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Add previous trajectories to vis_result function and check if vis/nba/ directory exists #8

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8 changes: 4 additions & 4 deletions test_nba.py
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Original file line number Diff line number Diff line change
Expand Up @@ -89,6 +89,8 @@ def draw_result(future,past,mode='pre'):
court = plt.imread("datasets/nba/court.png")
plt.imshow(court, zorder=0, extent=[Constant.X_MIN, Constant.X_MAX - Constant.DIFF,
Constant.Y_MAX, Constant.Y_MIN],alpha=0.5)
if not os.path.isdir("vis/nba/"):
os.makedirs("vis/nba/")
if mode == 'pre':
plt.savefig('vis/nba/'+str(idx)+'pre.png')
else:
Expand All @@ -103,6 +105,7 @@ def vis_result(test_loader, args):

for data in test_loader:
future_traj = np.array(data['future_traj']) * args.traj_scale # B,N,T,2
previous_3D = np.array(data['past_traj']) * args.traj_scale
with torch.no_grad():
prediction = model.inference(data)
prediction = prediction * args.traj_scale
Expand All @@ -117,7 +120,7 @@ def vis_result(test_loader, args):
best_guess = prediction[indices,np.arange(batch*actor_num)]
best_guess = np.reshape(best_guess, (batch,actor_num, args.future_length, 2))
gt = np.reshape(future_traj,(batch,actor_num,args.future_length, 2))
previous_3D = np.reshape(previous_3D,(batch,actor_num,args.future_length, 2))
previous_3D = np.reshape(previous_3D,(batch,actor_num,args.past_length, 2))

draw_result(best_guess,previous_3D)
draw_result(gt,previous_3D,mode='gt')
Expand Down Expand Up @@ -272,6 +275,3 @@ def test_model_all(test_loader, args):
vis_result(test_loader, args)

test_model_all(test_loader, args)