Python cv2.COLORMAP_RAINBOW Examples

The following are 5 code examples of cv2.COLORMAP_RAINBOW(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module cv2 , or try the search function .
Example #1
Source File: utility.py    From hmd with MIT License 6 votes vote down vote up 
def draw_anchors_rect(img_arr, anchor_posi, sample = 1, ratio = 1):
    ori_dtype = img_arr.dtype
    joint_num = len(anchor_posi)
    seed_arr = np.array([range(1,255,255/joint_num)]).astype(np.uint8)
    color_list = cv2.applyColorMap(seed_arr, cv2.COLORMAP_RAINBOW)[0]
    draw_arr = img_arr.astype(np.float)
    for i in range(joint_num):
        if (i%sample)!=0:
            continue
        draw_arr = draw_rect(draw_arr, anchor_posi[i], 
                             size = 32,
                             color = color_list[i].tolist())
    if ratio < 1:
        draw_arr = draw_arr*ratio + img_arr.astype(np.float)*(1-ratio)    
    return draw_arr.astype(ori_dtype)

# write OBJ from vertex
# not tested yet
Example #2
Source File: utility.py    From hmd with MIT License 5 votes vote down vote up 
def draw_joints_rect(img_arr, joint_posi, ratio = 1):
    ori_dtype = img_arr.dtype
    joint_num = len(joint_posi)
    seed_arr = np.array([range(1,255,255/joint_num)]).astype(np.uint8)
    color_list = cv2.applyColorMap(seed_arr, cv2.COLORMAP_RAINBOW)[0]
    draw_arr = img_arr.astype(np.float)
    for i in range(joint_num):
        draw_arr = draw_rect(draw_arr, joint_posi[i], 
                             color = color_list[i].tolist())
    if ratio < 1:
        draw_arr = draw_arr*ratio + img_arr.astype(np.float)*(1-ratio)
    return draw_arr.astype(ori_dtype)

# for visualizing predict window in images
Example #3
Source File: util.py    From deconvolution with GNU General Public License v3.0 5 votes vote down vote up 
def tensor2array(tensor, max_value=None, colormap='rainbow'):
    if max_value is None:
        tensor=(tensor-tensor.min())/(tensor.max()-tensor.min()+1e-6)
        max_value = tensor.max().item()
    if tensor.ndimension() == 2 or tensor.size(0) == 1:
        try:
            import cv2
            if cv2.__version__.startswith('3'):
                color_cvt = cv2.COLOR_BGR2RGB
            else:  # 2.4
                color_cvt = cv2.cv.CV_BGR2RGB
            if colormap == 'rainbow':
                colormap = cv2.COLORMAP_RAINBOW
            elif colormap == 'bone':
                colormap = cv2.COLORMAP_BONE
            array = (tensor.squeeze().numpy()*255./max_value).clip(0, 255).astype(np.uint8)
            colored_array = cv2.applyColorMap(array, colormap)
            array = cv2.cvtColor(colored_array, color_cvt).astype(np.float32)/255
        except ImportError:
            if tensor.ndimension() == 2:
                tensor.unsqueeze_(2)
            array = (tensor.expand(tensor.size(0), tensor.size(1), 3).numpy()/max_value).clip(0,1)

    elif tensor.ndimension() == 3:
        assert(tensor.size(0) == 3)
        array = 0.5 + tensor.numpy().transpose(1, 2, 0)*0.5

    #for tensorboardx 1.4
    #array=array.transpose(2,0,1)

    return array
Example #4
Source File: utils.py    From DPSNet with MIT License 5 votes vote down vote up 
def tensor2array(tensor, max_value=255, colormap='rainbow'):
    if max_value is None:
        max_value = tensor.max()
    if tensor.ndimension() == 2 or tensor.size(0) == 1:
        try:
            import cv2
            if cv2.__version__.startswith('2'): # 2.4
                color_cvt = cv2.cv.CV_BGR2RGB
            else:  
                color_cvt = cv2.COLOR_BGR2RGB
            if colormap == 'rainbow':
                colormap = cv2.COLORMAP_RAINBOW
            elif colormap == 'bone':
                colormap = cv2.COLORMAP_BONE
            array = (255*tensor.squeeze().numpy()/max_value).clip(0, 255).astype(np.uint8)
            colored_array = cv2.applyColorMap(array, colormap)
            array = cv2.cvtColor(colored_array, color_cvt).astype(np.float32)/255
            #array = array.transpose(2, 0, 1)
        except ImportError:
            if tensor.ndimension() == 2:
                tensor.unsqueeze_(2)
            array = (tensor.expand(tensor.size(0), tensor.size(1), 3).numpy()/max_value).clip(0,1)

    elif tensor.ndimension() == 3:
        #assert(tensor.size(0) == 3)
        #array = 0.5 + tensor.numpy()*0.5
        array = 0.5 + tensor.numpy().transpose(1,2,0)*0.5
    return array
Example #5
Source File: predict.py    From PSMNet-Tensorflow with MIT License 5 votes vote down vote up 
def main():

    height = 368 #544 #368
    weight = 1232 #960 #1232
    left_img = args.datapath+args.leftimg
    right_img = args.datapath+args.leftimg


    with tf.Session() as sess:


        img_L = cv2.cvtColor(cv2.imread(left_img), cv2.COLOR_BGR2RGB)
        img_L = cv2.resize(img_L, (weight, height))
        img_R = cv2.cvtColor(cv2.imread(right_img), cv2.COLOR_BGR2RGB)
        img_R = cv2.resize(img_R, (weight, height))		

        img_L = DataLoaderKITTI.mean_std(img_L)
        img_L = np.expand_dims(img_L, axis=0)
        img_R = DataLoaderKITTI.mean_std(img_R)
        img_R = np.expand_dims(img_R, axis=0)
		
        PSMNet = Model(sess, height=height, weight=weight, batch_size=args.batch, max_disp=args.maxdisp)
        saver = tf.train.Saver()
        saver.restore(sess, args.loadmodel)
		
        pred = PSMNet.predict(img_L, img_R)
        pred = np.squeeze(pred,axis=0)
        print(pred.shape)
        print(pred.max())
        #np.save('pred.npy',pred)
        
        pred_disp = pred.astype(np.uint8)
        print(pred_disp.shape)
        #pred_disp = np.squeeze(pred_disp,axis=0)
        cv2.imwrite('pred_disp.png', pred_disp)
        pred_rainbow = cv2.applyColorMap(pred_disp, cv2.COLORMAP_RAINBOW)
        cv2.imwrite('pred_rainbow.png', pred_rainbow)