dl and ur may still be flipped

selfdrive/modeld/models/dmonitoring.cc

@@ -114,8 +114,7 @@ DMonitoringResult dmonitoring_eval_frame(DMonitoringModelState* s, void* stream_
                     resized_width, resized_height,
                     mode);
 
-  // new, with prerotate
+  // prerotate to be cache aware
-
   uint8_t *resized_buf_rot = get_buffer(s->resized_buf_rot, resized_width*resized_height*3/2);
   uint8_t *resized_y_buf_rot = resized_buf_rot;
   uint8_t *resized_u_buf_rot = resized_y_buf_rot + (resized_width * resized_height);
@@ -127,7 +126,8 @@ DMonitoringResult dmonitoring_eval_frame(DMonitoringModelState* s, void* stream_
                      resized_y_buf_rot, resized_height,
                      resized_u_buf_rot, resized_height/2,
                      resized_v_buf_rot, resized_height/2,
-                     resized_width, resized_height, libyuv::kRotate90);
+                     // negative height causes a vertical flip to match previous
+                     resized_width, -resized_height, libyuv::kRotate90);
 
   int yuv_buf_len = (MODEL_WIDTH/2) * (MODEL_HEIGHT/2) * 6; // Y|u|v -> y|y|y|y|u|v
   float *net_input_buf = get_buffer(s->net_input_buf, yuv_buf_len);
@@ -136,13 +136,13 @@ DMonitoringResult dmonitoring_eval_frame(DMonitoringModelState* s, void* stream_
   for (int c = 0; c < MODEL_WIDTH/2; c++) {
     for (int r = 0; r < MODEL_HEIGHT/2; r++) {
       // Y_ul
-      net_input_buf[(c*MODEL_HEIGHT/2) + r + (0*(MODEL_WIDTH/2)*(MODEL_HEIGHT/2))] = input_lambda(resized_buf_rot[(2*r) + (2*c*resized_height)]);
+      net_input_buf[(c*MODEL_HEIGHT/2) + r + (0*(MODEL_WIDTH/2)*(MODEL_HEIGHT/2))] = input_lambda(resized_buf_rot[(2*r) + (2*c)*resized_height]);
       // Y_dl
-      net_input_buf[(c*MODEL_HEIGHT/2) + r + (1*(MODEL_WIDTH/2)*(MODEL_HEIGHT/2))] = input_lambda(resized_buf_rot[(2*r+1) + (2*c*resized_height)]);
+      net_input_buf[(c*MODEL_HEIGHT/2) + r + (1*(MODEL_WIDTH/2)*(MODEL_HEIGHT/2))] = input_lambda(resized_buf_rot[(2*r+1) + (2*c)*resized_height]);
       // Y_ur
-      net_input_buf[(c*MODEL_HEIGHT/2) + r + (2*(MODEL_WIDTH/2)*(MODEL_HEIGHT/2))] = input_lambda(resized_buf_rot[(2*r) + (2*c*resized_height+1)]);
+      net_input_buf[(c*MODEL_HEIGHT/2) + r + (2*(MODEL_WIDTH/2)*(MODEL_HEIGHT/2))] = input_lambda(resized_buf_rot[(2*r) + (2*c+1)*resized_height]);
       // Y_dr
-      net_input_buf[(c*MODEL_HEIGHT/2) + r + (3*(MODEL_WIDTH/2)*(MODEL_HEIGHT/2))] = input_lambda(resized_buf_rot[(2*r+1) + (2*c*resized_height+1)]);
+      net_input_buf[(c*MODEL_HEIGHT/2) + r + (3*(MODEL_WIDTH/2)*(MODEL_HEIGHT/2))] = input_lambda(resized_buf_rot[(2*r+1) + (2*c+1)*resized_height]);
       // U
       net_input_buf[(c*MODEL_HEIGHT/2) + r + (4*(MODEL_WIDTH/2)*(MODEL_HEIGHT/2))] = input_lambda(resized_buf_rot[(resized_width*resized_height) + r + (c*resized_height/2)]);
       // V
@@ -150,34 +150,15 @@ DMonitoringResult dmonitoring_eval_frame(DMonitoringModelState* s, void* stream_
     }
   }
 
-  // old rotation
-
-  /*int yuv_buf_len = (MODEL_WIDTH/2) * (MODEL_HEIGHT/2) * 6; // Y|u|v -> y|y|y|y|u|v
-  float *net_input_buf = get_buffer(s->net_input_buf, yuv_buf_len);
-  // one shot conversion, O(n) anyway
-  // yuvframe2tensor, normalize
-  for (int c = 0; c < MODEL_WIDTH/2; c++) {
-    for (int r = 0; r < MODEL_HEIGHT/2; r++) {
-      // Y_ul
-      net_input_buf[(c*MODEL_HEIGHT/2) + r] = input_lambda(resized_buf[(2*r*resized_width) + (2*c)]);
-      // Y_ur
-      net_input_buf[(c*MODEL_HEIGHT/2) + r + (2*(MODEL_WIDTH/2)*(MODEL_HEIGHT/2))] = input_lambda(resized_buf[(2*r*resized_width) + (2*c+1)]);
-      // Y_dl
-      net_input_buf[(c*MODEL_HEIGHT/2) + r + ((MODEL_WIDTH/2)*(MODEL_HEIGHT/2))] = input_lambda(resized_buf[(2*r*resized_width+1) + (2*c)]);
-      // Y_dr
-      net_input_buf[(c*MODEL_HEIGHT/2) + r + (3*(MODEL_WIDTH/2)*(MODEL_HEIGHT/2))] = input_lambda(resized_buf[(2*r*resized_width+1) + (2*c+1)]);
-      // U
-      net_input_buf[(c*MODEL_HEIGHT/2) + r + (4*(MODEL_WIDTH/2)*(MODEL_HEIGHT/2))] = input_lambda(resized_buf[(resized_width*resized_height) + (r*resized_width/2) + c]);
-      // V
-      net_input_buf[(c*MODEL_HEIGHT/2) + r + (5*(MODEL_WIDTH/2)*(MODEL_HEIGHT/2))] = input_lambda(resized_buf[(resized_width*resized_height) + ((resized_width/2)*(resized_height/2)) + (r*resized_width/2) + c]);
-    }
-  }*/
-
   //printf("preprocess completed. %d \n", yuv_buf_len);
   //FILE *dump_yuv_file = fopen("/tmp/rawdump.yuv", "wb");
   //fwrite(raw_buf, height*width*3/2, sizeof(uint8_t), dump_yuv_file);
   //fclose(dump_yuv_file);
 
+  // *** testing ***
+  // idat = np.frombuffer(open("/tmp/inputdump.yuv", "rb").read(), np.float32).reshape(6, 160, 320)
+  // imshow(cv2.cvtColor(tensor_to_frames(idat[None]/0.0078125+128)[0], cv2.COLOR_YUV2RGB_I420))
+
   //FILE *dump_yuv_file2 = fopen("/tmp/inputdump.yuv", "wb");
   //fwrite(net_input_buf, MODEL_HEIGHT*MODEL_WIDTH*3/2, sizeof(float), dump_yuv_file2);
   //fclose(dump_yuv_file2);