fix tflitemicro_person_detection

examples/tflitemicro_person_detection/tflu_person_detection/image_provider.h

@@ -0,0 +1,40 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_MICRO_EXAMPLES_PERSON_DETECTION_EXPERIMENTAL_IMAGE_PROVIDER_H_
+#define TENSORFLOW_LITE_MICRO_EXAMPLES_PERSON_DETECTION_EXPERIMENTAL_IMAGE_PROVIDER_H_
+
+#include "tensorflow/lite/c/common.h"
+#include "tensorflow/lite/micro/micro_error_reporter.h"
+
+// This is an abstraction around an image source like a camera, and is
+// expected to return 8-bit sample data.  The assumption is that this will be
+// called in a low duty-cycle fashion in a low-power application.  In these
+// cases, the imaging sensor need not be run in a streaming mode, but rather can
+// be idled in a relatively low-power mode between calls to GetImage().  The
+// assumption is that the overhead and time of bringing the low-power sensor out
+// of this standby mode is commensurate with the expected duty cycle of the
+// application.  The underlying sensor may actually be put into a streaming
+// configuration, but the image buffer provided to GetImage should not be
+// overwritten by the driver code until the next call to GetImage();
+//
+// The reference implementation can have no platform-specific dependencies, so
+// it just returns a static image. For real applications, you should
+// ensure there's a specialized implementation that accesses hardware APIs.
+TfLiteStatus GetImage(tflite::ErrorReporter* error_reporter, int image_width,
+                      int image_height, int channels, int8_t* image_data, 
+					  uint8_t * hardware_input);
+
+#endif  // TENSORFLOW_LITE_MICRO_EXAMPLES_PERSON_DETECTION_EXPERIMENTAL_IMAGE_PROVIDER_H_