*
* 'tensor_filter' for image recognition.
* Download tflite moel 'Mobilenet_1.0_224_quant' from below link,
- * https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/lite/g3doc/models.md#image-classification-quantized-models
+ * https://github.com/nnsuite/testcases/tree/master/DeepLearningModels/tensorflow-lite/Mobilenet_v1_1.0_224_quant
*
* 'tensor_sink' updates recognition result to display in textoverlay.
*
main (int argc, char **argv)
{
const gchar tflite_model_path[] = "./tflite_model";
- /** 224x224 for tflite model */
- const guint width = 224;
- const guint height = 224;
gchar *str_pipeline;
gulong handle_id;
"video/x-raw,width=640,height=480,format=RGB ! tee name=t_raw "
"t_raw. ! queue ! textoverlay name=tensor_res font-desc=Sans,24 ! "
"videoconvert ! ximagesink name=img_tensor "
- "t_raw. ! queue leaky=2 max-size-buffers=2 ! videoscale ! video/x-raw,width=%d,height=%d ! tensor_converter ! "
+ "t_raw. ! queue leaky=2 max-size-buffers=2 ! videoscale ! tensor_converter ! "
"tensor_filter framework=tensorflow-lite model=%s ! "
"tensor_sink name=tensor_sink",
- width, height, g_app.tflite_info.model_path);
+ g_app.tflite_info.model_path);
g_app.pipeline = gst_parse_launch (str_pipeline, NULL);
g_free (str_pipeline);
_check_cond_err (g_app.pipeline != NULL);
'tensor_filter' for image recognition.
Download tflite moel 'Mobilenet_1.0_224_quant' from below link,
-https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/lite/g3doc/models.md#image-classification-quantized-models
+https://github.com/nnsuite/testcases/tree/master/DeepLearningModels/tensorflow-lite/Mobilenet_v1_1.0_224_quant
'tensor_sink' updates recognition result to display in textoverlay.
'video/x-raw,width=640,height=480,format=RGB ! tee name=t_raw '
't_raw. ! queue ! textoverlay name=tensor_res font-desc=Sans,24 ! '
'videoconvert ! ximagesink name=img_tensor '
- 't_raw. ! queue leaky=2 max-size-buffers=2 ! videoscale ! video/x-raw,width=224,height=224 ! tensor_converter ! '
+ 't_raw. ! queue leaky=2 max-size-buffers=2 ! videoscale ! tensor_converter ! '
'tensor_filter framework=tensorflow-lite model=' + self.tflite_model + ' ! '
'tensor_sink name=tensor_sink'
)