img = cv2.resize(img, (scaled_width, max_res))
curr_frame = img[:, width_crop: width_crop + max_res]
else:
curr_frame = img[height_crop : height_crop + max_res,
width_crop: width_crop + max_res]
curr_frame = curr_frame.astype(numpy.int16)
old_ref[:] = ref_frame
spikes, ref_frame, abs_diff = generate_spikes(curr_frame=curr_frame, ref_frame=ref_frame,
#~ threshold=threshold,
min_threshold=min_threshold,
max_threshold=max_threshold,
threshold_matrix=threshold_matrix,
down_threshold_change=threshold_delta_down,
up_threshold_change=threshold_delta_up,
width=max_res, height=max_res,
inh_width=inh_width,
polarity=polarity,
max_time_ms=max_time_ms,
inh_coords=inh_coords,
inhibition=inhibit)
neg_spikes, pos_spikes, global_max = split_spikes(spikes, abs_diff, polarity)
lists = make_spike_lists_rate(pos_spikes, neg_spikes,
global_max,
up_down_shift, data_shift, data_mask,
max_time_ms)
spikes_frame = render_frame(spikes=spikes, curr_frame=curr_frame,
width_crop: width_crop + max_res]
curr_frame = curr_frame.astype(numpy.int16)
old_ref[:] = out_ref
print("first pixels of ref = %s"%(old_ref[0, :10]))
spikes, ref_frame, abs_diff, \
out_ref, threshold_matrix = generate_spikes(curr_frame=curr_frame,
ref_frame=ref_frame,
out_ref=out_ref,
threshold=threshold,
min_threshold=min_threshold,
max_threshold=max_threshold,
threshold_matrix=threshold_matrix,
down_threshold_change=threshold_delta_down,
up_threshold_change=threshold_delta_up,
width=max_res, height=max_res,
inh_width=inh_width,
polarity=polarity,
max_time_ms=max_time_ms,
inh_coords=inh_coords,
num_bits=bits_idx,
noise_probability=noise_prob,
update_weight=update_weight,
log2_table=log2_table[bits_idx-1],
inhibition=inhibit)
neg_spikes, pos_spikes, global_max = split_spikes(spikes, abs_diff, polarity)
lists = make_spike_lists_rate(pos_spikes, neg_spikes,
