docs: Custom README

README.md

@@ -1,14 +1,67 @@
 ---
 library_name: keras
+tags:
+- burmese
+- burma
+- myanmar
+- snake
+- classifier
 ---
 
 ## Model description
 
-More information needed
+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
+
+```
 
 ## Intended uses & limitations
 
-More information needed
+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.
 
 ## Training and evaluation data