Push Keras model using huggingface_hub.

README.md

@@ -1,67 +1,14 @@
 ---
 library_name: keras
-tags:
-- burmese
-- burma
-- myanmar
-- snake
-- classifier
 ---
 
 ## Model description
 
-MM DeepSnake is an artificial intelligence project to classify snake species in Myanmar. 
-We collect images all around Myanmar for training our model.
-
-Current Version - **Alpha - 1.0.0**
-
-Currently our model can understand **10** species of snakes. Some of the snakes are very much in species and hard to classify individual species. Therefore, we took genus as a categories.
-
-At the moment, we support
-- Trimeresurus_sp (Asian Palm Pit vipers) - မြွေစိမ်းမြီးခြောက်
-- Rhadophis helleri (Heller Red necked keelback) - လည်ပင်းနီမြွေ
-- Lycodon aulicus (Wolf Snake) - မြွေဝံပုလွေ
-- Fowlea piscator (Checkered Keelback) - ရေမြွေဗျောက်မ
-- Daboia siamensis (Eastern Russell's viper) - မြွေပွေး
-- Chrysopelea ornata (Golden Tree Snake) - ထန်းမြွေ
-- Bungarus fasciatus (Banded Krait) - ငန်းတော်ကြား
-- Ophiophagus hannah(King Cobra) - တောကြီးမြွေဟောက်
-- Laticauda colubrina (Sea Snake) - ဂျက်မြွေ
-- Naja kaouthia (Cobra) - မြွေဟောက်
-
-
-Here is sample code to use burmese_snake_classifier
-
-```python
-import numpy as np
-import tensorflow as tf
-from huggingface_hub import from_pretrained_keras
-
-pretrained_model = from_pretrained_keras('jojo-ai-mst/burmese_snake_classifier')
-
-class_names = ['Bungarus fasciatus (Banded Krait)', 'Chrysopelea ornata (Golden Tree Snake)', "Daboia siamensis (Eastern Russell's viper)", 'Fowlea piscator (Checkered Keelback)', 'Laticauda colubrina (Sea Snake)', 'Lycodon aulicus (Wolf Snake)', 'Naja kaouthia(Cobra)', 'Ophiophagus_hannah(King Cobra)', 'Rhadophis helleri (Heller Red necked keelback)', 'Trimeresurus_sp (Asian Palm Pit vipers)']
-
-def softmax_stable(x):
-    return(np.exp(x - np.max(x)) / np.exp(x - np.max(x)).sum())
-
-def predict_img(input_img):
-  img_array = np.expand_dims(input_img, 0) 
-  predictions = pretrained_model.predict(img_array)
-  score = tf.nn.softmax(predictions[0])
-
-  result =  "This image most likely belongs to {} with a {:.2f} percent confidence.".format(class_names[np.argmax(score)], 100 * np.max(score))
-
-  return result
-
-```
+More information needed
 
 ## Intended uses & limitations
 
-This model is open source for open source projects.
-Project that modifies, extends, derives from this model must mention the original model **jojo-ai-mst/burmese_snake_classifier**.
-Commercial use needs to be requested to the model contributor **jojo-ai-mst**.
-
-We strongly alert that every **snake bite** case should go to professional medical staffs.
+More information needed
 
 ## Training and evaluation data
 

fingerprint.pb

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saved_model.pb

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variables/variables.data-00000-of-00001

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