Monicet animals model

app.py

@@ -1,7 +1,31 @@
 import gradio as gr
+import numpy as np
+import os
+import PIL
 
-def greet(name):
-    return "Hello " + name + "!!"
+import tensorflow as tf
+from tensorflow import keras
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+def predict(img):
+  img_cropped = np.array(img, dtype='float32')[:100, 15:-15, :] / 255
+  img_bw = np.mean(img_cropped, axis=-1)
+
+  # predict
+  img_input = np.expand_dims(img_bw, axis=0)
+  prediction = model.predict(img_input)[0]
+  animals = ['common bottlenose dolphin', 'fin whale', 'risso dolphin', 'short finned pilot whale', 'sperm whale']
+
+  #bw image for display
+  im = PIL.Image.fromarray(np.uint8(img_bw*255))
+
+  return [{animals[i]: float(prediction[i]) for i in range(len(animals))}, im]
+
+
+model = keras.models.load_model('model')
+
+iface = gr.Interface(predict,\
+                     inputs = gr.Image(shape=(130, 120)),\
+                     outputs = [gr.outputs.Label(num_top_classes=5),\
+                                gr.Image(shape=(100, 100), image_mode='L')])
+
+iface.launch()

model/keras_metadata.pb

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:98551dbae106811bc2c33bf7e0927fe5466a98d12dbd6f43ca1a2153a5cc25af
+size 32822

model/saved_model.pb

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5670f4e19cd462fac3777e9334cbe9bfcefb5949c0c3ae2f1b579c26e6352d7e
+size 434207