Update README.md

README.md

@@ -16,6 +16,113 @@ base_model:
 
 # Perch
 
-tflite and onnx format of the Perch v2 model.
+tflite and munually optimized onnx format of the Perch v2 model.
 
 Source https://www.kaggle.com/models/google/bird-vocalization-classifier/
+
+## Model information
+
+```
+ONNX Model Information:
+Inputs:
+  - Name: inputs, Shape: ['batch', 160000], Type: tensor(float)
+Outputs:
+  - Name: embedding, Shape: ['batch', 1536], Type: tensor(float)
+  - Name: spatial_embedding, Shape: ['batch', 16, 4, 1536], Type: tensor(float)
+  - Name: spectrogram, Shape: ['batch', 500, 128], Type: tensor(float)
+  - Name: label, Shape: ['batch', 14795], Type: tensor(float)
+
+TFLite Model Information:
+Inputs:
+  - Name: serving_default_inputs:0, Shape: [     1 160000], Type: <class 'numpy.float32'>
+Outputs:
+  - Name: StatefulPartitionedCall:0, Shape: [   1 1536], Type: <class 'numpy.float32'>
+  - Name: StatefulPartitionedCall:2, Shape: [   1   16    4 1536], Type: <class 'numpy.float32'>
+  - Name: StatefulPartitionedCall:3, Shape: [  1 500 128], Type: <class 'numpy.float32'>
+  - Name: StatefulPartitionedCall:1, Shape: [    1 14795], Type: <class 'numpy.float32'>
+
+Generating random inputs:
+  - inputs: shape=(1, 160000), dtype=float32
+
+Running ONNX model inference...
+Running TFLite model inference...
+
+================================================================================
+COMPARISON RESULTS
+================================================================================
+
+Output 0:
+  ONNX Runtime shape: (1, 1536), dtype: float32
+  TFLite shape:       (1, 1536), dtype: float32
+
+  ONNX Runtime vs TFLite:
+    Max difference:  0.0000007208
+    Mean difference: 0.0000001543
+    Relative tolerance: 1e-05
+    Absolute tolerance: 1e-05
+    ✅ Outputs match within tolerance
+
+Output 1:
+  ONNX Runtime shape: (1, 16, 4, 1536), dtype: float32
+  TFLite shape:       (1, 16, 4, 1536), dtype: float32
+
+  ONNX Runtime vs TFLite:
+    Max difference:  0.0000131130
+    Mean difference: 0.0000005482
+    Relative tolerance: 1e-05
+    Absolute tolerance: 1e-05
+    ✅ Outputs match within tolerance
+
+Output 2:
+  ONNX Runtime shape: (1, 500, 128), dtype: float32
+  TFLite shape:       (1, 500, 128), dtype: float32
+
+  ONNX Runtime vs TFLite:
+    Max difference:  0.0000005960
+    Mean difference: 0.0000000100
+    Relative tolerance: 1e-05
+    Absolute tolerance: 1e-05
+    ✅ Outputs match within tolerance
+
+Output 3:
+  ONNX Runtime shape: (1, 14795), dtype: float32
+  TFLite shape:       (1, 14795), dtype: float32
+
+  ONNX Runtime vs TFLite:
+    Max difference:  0.0000152588
+    Mean difference: 0.0000014861
+    Relative tolerance: 1e-05
+    Absolute tolerance: 1e-05
+    ✅ Outputs match within tolerance
+
+================================================================================
+✅ ALL OUTPUTS MATCH!
+================================================================================
+
+Benchmarking ONNX model (10 warmup + 100 test runs)...
+Benchmarking TFLite model (10 warmup + 100 test runs)...
+
+================================================================================
+BENCHMARK RESULTS
+================================================================================
+
+ONNX Model:
+  Mean:   66.350 ms
+  Median: 66.339 ms
+  Std:    2.160 ms
+  Min:    61.801 ms
+  Max:    74.614 ms
+
+TFLite Model:
+  Mean:   608.777 ms
+  Median: 606.753 ms
+  Std:    11.304 ms
+  Min:    602.735 ms
+  Max:    684.807 ms
+
+Comparison:
+  ONNX Runtime is 9.18x faster than TFLite
+  Difference: 542.427 ms
+================================================================================
+```
+