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,