Updated DTutils and folder simultarion (logs, reception errors, etc)
This commit is contained in:
Emilio Martinez
parent
acd5afa624
commit
25921298c3
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@ -22,6 +22,9 @@ from scipy import signal
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from PIL import Image
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from utils.DTutils import TMDS_encoding_original, TMDS_serial
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import sys
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import logging
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from utils import utils_logger
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from datetime import datetime
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#%%
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@ -47,7 +50,7 @@ def image_transmition_simulation(I, blanking=False):
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return I_TMDS_Tx, I_TMDS.shape
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def image_capture_simulation(I_Tx, h_total, v_total, N_harmonic, noise_std=0,
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fps=60):
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fps=60, freq_error=0, phase_error=0):
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# Compute pixelrate and bitrate
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px_rate = h_total*v_total*fps
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@ -75,13 +78,14 @@ def image_capture_simulation(I_Tx, h_total, v_total, N_harmonic, noise_std=0,
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# AM modulation frequency according to pixel harmonic
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harm = N_harmonic*px_rate
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# Harmonic oscilator
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baseband_exponential = np.exp(2j*np.pi*harm*t_continuous)
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# Harmonic oscilator (including frequency and phase error)
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baseband_exponential = np.exp(2j*np.pi*(harm+freq_error)*t_continuous + 1j*phase_error)
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usrp_rate = 50e6
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usrp_BW = usrp_rate/2
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# AM modulation and SDR sampling
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I_Rx = signal.resample_poly(I_Tx_noisy*baseband_exponential,up=int(usrp_rate), down=sample_rate)
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I_Rx = signal.resample_poly(I_Tx_noisy*baseband_exponential,up=int(usrp_BW), down=sample_rate)
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# Reshape signal to the image size
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I_capture = signal.resample(I_Rx, h_total*v_total).reshape(v_total,h_total)
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@ -97,58 +101,81 @@ def save_simulation_image(I,path_and_name):
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I_real = np.real(I)
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I_imag = np.imag(I)
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realmax = I_real.max()
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realmin = I_real.min()
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imagmax = I_imag.max()
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imagmin = I_imag.min()
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# Stretch contrast on every channel
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I_save[:,:,0] = 255*(I_real-realmin)/(realmax-realmin)
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I_save[:,:,1] = 255*(I_imag-imagmin)/(imagmax-imagmin)
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I_save[:,:,0], I_save[:,:,1] = I_real, I_imag
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min_value, max_value = np.min(I_save[:,:,:2]), np.max(I_save[:,:,:2])
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I_save[:,:,0] = 255*(I_real-min_value)/(max_value-min_value)
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I_save[:,:,1] = 255*(I_imag-min_value)/(max_value-min_value)
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im = Image.fromarray(I_save.astype('uint8'))
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im.save(path_and_name)
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def main():
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logs_dir = './logfiles/'
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# Create logs directory if not exist
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if not os.path.exists(logs_dir):
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os.mkdir(logs_dir)
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logger_name = 'simulations_'+datetime.now().strftime("%d-%m-%Y_%H:%M:%S")
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utils_logger.logger_info(logger_name, logs_dir+logger_name+'.log')
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logger = logging.getLogger(logger_name)
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# Get foldername argument
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foldername = sys.argv[-1]
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message = f'Tempest capture simulation for image folder {foldername}\n'
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logger.info(message)
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# Get images and subfolders names
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images = get_images_names_from_folder(foldername)
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simulations_folder = foldername+'/simulations/'
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os.mkdir(simulations_folder)
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# Create simulation directory if not exist at the folder path
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simulations_path = foldername+'/simulations/'
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if not os.path.exists(simulations_path):
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os.mkdir(simulations_path)
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message = f'Created simulation directory at {simulations_path}\n'
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logger.info(message)
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# timestamp for simulation starting
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t1_image = time.time()
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# Possible noise std values
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# noise_stds = np.array([ 0, 5, 10, 15, 20, 25])
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for image in images:
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# timestamp for simulation starting
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t1_image = time.time()
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# Read image
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image_path = foldername+'/'+image
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I = imread(image_path)
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# TMDS coding and bit serialization
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I_Tx, resolution = image_transmition_simulation(I)
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v_res, h_res, _ = resolution
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# Choose random pixelrate harmonic number
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N_harmonic = np.random.randint(1,10)
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message = f'Initiate simulation for image {image} with {N_harmonic} pixel harmonic frequency'
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logger.info(message)
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# TMDS coding and bit serialization
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I_Tx, resolution = image_transmition_simulation(I, blanking=True)
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v_res, h_res, _ = resolution
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I_capture = image_capture_simulation(I_Tx, h_res, v_res, N_harmonic)
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path = simulations_folder+image
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path = simulations_path+image
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save_simulation_image(I_capture,path)
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# timestamp for simulation ending
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t2_image = time.time()
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# timestamp for simulation ending
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t2_image = time.time()
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t_images = t2_image-t1_image
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message = 'Processing time: {:.2f}'.format(t_images)+'s\n'
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logger.info(message)
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t_images = t2_images-t1_images
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print('\nTiempo total de las '+str(len(images))+' simulaciones:','{:.2f}'.format(t_images)+'s\n')
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if __name__ == "__main__":
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main()
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@ -106,37 +106,37 @@ def TMDS_pixel_rare (pix):
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Outputs:
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- pix_out: TDMS coded 16-bit pixel (only 10 useful)
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- cnt: 0's and 1's balance updated with new pixel coding
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- cnt: 0's and 1's balance updated with new pixel coding
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"""
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# Convert 8-bit pixel to binary list D
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D = uint8_to_binarray(pix)
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d = uint8_to_binarray(pix)
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# Initialize output q
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qm = [D[0]]
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Qm = [d[0]]
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# 1's unbalanced condition at current pixel
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N1_D = np.sum(D)
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N1_D = np.sum(d)
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if N1_D>4 or (N1_D==4 and not(D[0])):
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if N1_D>4 or (N1_D==4 and not(d[0])):
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# XNOR of consecutive bits
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for k in range(1,8):
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qm.append( not(qm[k-1] ^ D[k]) )
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qm.append(0)
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Qm.append( not(Qm[k-1] ^ d[k]) )
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Qm.append(0)
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else:
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# XOR of consecutive bits
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for k in range(1,8):
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qm.append( qm[k-1] ^ D[k] )
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qm.append(1)
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Qm.append( Qm[k-1] ^ d[k] )
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Qm.append(1)
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qm.append(np.random.choice([0,1]))
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Qm.append(np.random.choice([0,1]))
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# Return the TMDS coded pixel as uint and 0's y 1's balance
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return binarray_to_uint(qm)
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return binarray_to_uint(Qm)
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@jit(nopython=True)
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def TMDS_pixel_numba(pix:uint8, cnt:int8)->tuple:
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@ -293,11 +293,11 @@ def TMDS_encoding_original (I, blanking = False):
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if blanking:
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# Get blanking resolution for input image
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v = (v_in==1080)*1125 + (v_in==720)*750 + (v_in==600)*628 + (v_in==480)*525
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h = (h_in==1920)*2200 + (h_in==1280)*1650 + (h_in==800)*1056 + (h_in==640)*800
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v = (v_in==1080)*1125 + (v_in==900)*1000 + (v_in==720)*750 + (v_in==600)*628 + (v_in==480)*525
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h = (h_in==1920)*2200 + (h_in==1600)*1800 + (h_in==1280)*1650 + (h_in==800)*1056 + (h_in==640)*800
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vdiff = v - v_in
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hdiff = h - h_in
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v_diff = v - v_in
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h_diff = h - h_in
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# Create image with blanking and change type to uint16
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# Assuming the blanking corresponds to 10bit number [0, 0, 1, 0, 1, 0, 1, 0, 1, 1] (LSB first)
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