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README.md

@@ -7,10 +7,12 @@ tags:
 
 # Kindwise Crossroad Model
 
-## The model use it
+## How to use
 
 Here is how to use this model to classify an image into one of the basic classes:
 
+### PyTorch
+
 ```python
 from huggingface_hub import hf_hub_download
 import cv2
@@ -64,3 +66,35 @@ Output:
     insect: 0.1%
   mushroom: 0.0%
 ```
+
+###
+
+### TensorFlow Lite
+
+```python
+from huggingface_hub import hf_hub_download
+import numpy as np
+import tensorflow as tf
+
+MODEL_PATH = hf_hub_download('kindwise/crossroad.tiny', 'model.tflite')  # or model.optimized.tflite
+
+INTERPRETER = tf.lite.Interpreter(model_path=MODEL_PATH)
+INTERPRETER.allocate_tensors()
+
+image_array_resized = ... # see the previous example
+tf_input = np.expand_dims(  # add batch dimension
+    (image_array_resized / 255).astype(np.float32),  # image values in [0..1]
+    0,
+)
+input_details = INTERPRETER.get_input_details()
+output_details = INTERPRETER.get_output_details()
+INTERPRETER.set_tensor(
+    input_details[0]['index'],
+    tf_input,
+)
+INTERPRETER.invoke()
+logits = INTERPRETER.get_tensor(output_details[0]['index'])[0]
+prediction = tf.nn.sigmoid(logits).numpy()
+for i in (-prediction).argsort():
+    print(f'{classes[i]:>10}: {100 * prediction[i]:.1f}%')
+```