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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
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README.md

@@ -10,4 +10,9 @@ pinned: false
 license: apache-2.0
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference <br/>
+
+Huggingface space app url: https://huggingface.co/spaces/Rhasan97/snake-recognizer 
+
+Gradio app url: https://6a9b80fbd65c303307.gradio.live 
+

app.ipynb

@@ -0,0 +1 @@
+{"cells":[{"cell_type":"code","execution_count":1,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":24668,"status":"ok","timestamp":1689000797969,"user":{"displayName":"Ragib Hasan","userId":"16758650432635137333"},"user_tz":-360},"id":"X2pitY6vCIVV","outputId":"0298f2d3-962e-4551-e363-b0e2a5932bb3"},"outputs":[],"source":["!pip install -Uqq fastai gradio nbdev"]},{"cell_type":"code","execution_count":null,"metadata":{"executionInfo":{"elapsed":8113,"status":"ok","timestamp":1689000837789,"user":{"displayName":"Ragib Hasan","userId":"16758650432635137333"},"user_tz":-360},"id":"yqZC0_6iCLCK"},"outputs":[],"source":["from fastai.vision.all import *"]},{"cell_type":"code","execution_count":null,"metadata":{"executionInfo":{"elapsed":1171,"status":"ok","timestamp":1689000869190,"user":{"displayName":"Ragib Hasan","userId":"16758650432635137333"},"user_tz":-360},"id":"Um42FYRoCLEs"},"outputs":[],"source":["from fastai.vision.all import load_learner\n","import gradio as gr"]},{"cell_type":"code","execution_count":6,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":28739,"status":"ok","timestamp":1689000990325,"user":{"displayName":"Ragib Hasan","userId":"16758650432635137333"},"user_tz":-360},"id":"o3Dp-zyPTHuu","outputId":"8bd925d8-6e07-445b-81b8-a863b3be19d3"},"outputs":[{"name":"stdout","output_type":"stream","text":["Mounted at /content/drive\n","/content/drive/My Drive/Snake Recognizer Project\n"]}],"source":["from google.colab import drive\n","drive.mount('/content/drive')\n","%cd /content/drive/My Drive/Snake Recognizer Project\n"]},{"cell_type":"code","execution_count":7,"metadata":{"executionInfo":{"elapsed":2905,"status":"ok","timestamp":1689001005562,"user":{"displayName":"Ragib Hasan","userId":"16758650432635137333"},"user_tz":-360},"id":"fQKBMX3YCLHT"},"outputs":[],"source":["model = load_learner('models/snake-recognizer-v0.pkl')"]},{"cell_type":"code","execution_count":8,"metadata":{"executionInfo":{"elapsed":437,"status":"ok","timestamp":1689001082262,"user":{"displayName":"Ragib Hasan","userId":"16758650432635137333"},"user_tz":-360},"id":"u43jOhZeCLKG"},"outputs":[],"source":["snake_labels = (\n","    \"Monocled cobra\",\n","    \"Egyptian cobra\",\n","    \"Black-necked spitting cobra\",\n","    \"Samar cobra\",\n","    \"Red spitting cobra\",\n","    \"Javan spitting cobra\",\n","    \"Spectacled cobra\",\n","    \"Russell's viper\",\n","    \"Horned vipers\",\n","    \"Bush vipers\",\n","    \"Eyelash viper\",\n","    \"Saw-scaled vipers\",\n","    \"Banded krait\",\n","    \"Black mamba\",\n","    \"Inland taipan\",\n","    \"Eastern brown snake\",\n","    \"Rattle snake\",\n","    \"King cobra\"\n",")\n","\n","def recognize_snake(photo):\n","  pred, idx, probs = model.predict(photo)\n","  return dict(zip(snake_labels, map(float, probs)))"]},{"cell_type":"code","execution_count":10,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":145},"executionInfo":{"elapsed":1134,"status":"ok","timestamp":1689001250714,"user":{"displayName":"Ragib Hasan","userId":"16758650432635137333"},"user_tz":-360},"id":"g2jgcw6eCLMs","outputId":"9a1aebd1-a555-4f90-ae89-58171d718a60"},"outputs":[{"data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAMAAAACACAIAAADS5vE8AAAmyGVYSWZNTQAqAAAACAAHAQ8AAgAAAAYAAAhuARAAAgAAABwAAAh0ARIAAwAAAAEAAQAAATIAAgAAABQAAAiQAhMAAwAAAAEAAgAAh2kABAAAAAEAAAik6hwABwAACAwAAABiAAAAABzqAAAACAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQ2Fub24AQ2Fub24gRU9TIERJR0lUQUwgUkVCRUwgWFRpADIwMDY6MDg6MjYgMTQ6NTg6MzEAACCCmgAFAAAAAQAAEjaCnQAFAAAAAQAAEj6IIgADAAAAAQACAACIJwADAAAAAQGQAACQAAAHAAAABDAyMjGQAwACAAAAFAAAEkaQBAACAAAAFAAAElqRAQAHAAAABAECAwCSAQAFAAAAAQAAEm6SAgAFAAAAAQAAEnaSBAAFAAAAAQAAEn6SBwADAAAAAQAFAACSCQADAAAAAQAQAACSCgAFAAAAAQAAEoaSfAAHAAATDAAAEo6ShgAHAAABCAAAJZqSkQACAAAAAzAwAACSkgACAAAAAzAwAACgAAAHAAAABDAxMDCgAQADAAAAAQABAACgAgADAAAAAQ8wAACgAwADAAAAAQogAACgBQAEAAAAAQAAJqKiDgAFAAAAAQAAJraiDwAFAAAAAQAAJr6iEAADAAAAAQACAACkAQADAAAAAQAAAACkAgADAAAAAQAAAACkAwADAAAAAQAAAACkBgADAAAAAQAAAADqHAAHAAAIDAAACirqHQAJAAAAAQAAEDwAAAAAHOoAAAAIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA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","text/plain":["PILImage mode=RGB size=192x128"]},"execution_count":10,"metadata":{},"output_type":"execute_result"}],"source":["img = PILImage.create(f'test data/black-necked-spitting-cobra-naja-nigricollis-wklein.jpg')\n","img.thumbnail((192,192))\n","img"]},{"cell_type":"code","execution_count":11,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":329},"executionInfo":{"elapsed":1004,"status":"ok","timestamp":1689001257595,"user":{"displayName":"Ragib Hasan","userId":"16758650432635137333"},"user_tz":-360},"id":"8LLOH8NACLPM","outputId":"215cec78-a7f0-4bab-91bb-ccd3861ae3ec"},"outputs":[{"data":{"text/html":["\n","<style>\n","    /* Turns off some styling */\n","    progress {\n","        /* gets rid of default border in Firefox and Opera. */\n","        border: none;\n","        /* Needs to be in here for Safari polyfill so background images work as expected. */\n","        background-size: auto;\n","    }\n","    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n","        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n","    }\n","    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n","        background: #F44336;\n","    }\n","</style>\n"],"text/plain":["<IPython.core.display.HTML object>"]},"metadata":{},"output_type":"display_data"},{"data":{"text/html":[],"text/plain":["<IPython.core.display.HTML object>"]},"metadata":{},"output_type":"display_data"},{"data":{"text/plain":["{'Monocled cobra': 1.1163722774654161e-05,\n"," 'Egyptian cobra': 0.01258796826004982,\n"," 'Black-necked spitting cobra': 0.9777340292930603,\n"," 'Samar cobra': 3.01445834338665e-05,\n"," 'Red spitting cobra': 2.3122642232920043e-05,\n"," 'Javan spitting cobra': 0.0005188836948946118,\n"," 'Spectacled cobra': 0.00015094962145667523,\n"," \"Russell's viper\": 9.27890941966325e-05,\n"," 'Horned vipers': 9.545711509417742e-05,\n"," 'Bush vipers': 0.0009361603297293186,\n"," 'Eyelash viper': 0.0003364287840668112,\n"," 'Saw-scaled vipers': 6.700432277284563e-05,\n"," 'Banded krait': 0.00015121301112230867,\n"," 'Black mamba': 0.0050192344933748245,\n"," 'Inland taipan': 7.476512109860778e-05,\n"," 'Eastern brown snake': 0.0020968415774405003,\n"," 'Rattle snake': 8.099497790681198e-06,\n"," 'King cobra': 6.572777056135237e-05}"]},"execution_count":11,"metadata":{},"output_type":"execute_result"}],"source":["recognize_snake(img)"]},{"cell_type":"code","execution_count":15,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":8658,"status":"ok","timestamp":1689001813938,"user":{"displayName":"Ragib Hasan","userId":"16758650432635137333"},"user_tz":-360},"id":"2hRElCiGCLSQ","outputId":"f1793d67-5dbf-4602-b5b5-834dfdc3e35f"},"outputs":[{"name":"stderr","output_type":"stream","text":["<ipython-input-15-5c2c720474bc>:1: GradioDeprecationWarning: Usage of gradio.inputs is deprecated, and will not be supported in the future, please import your component from gradio.components\n","  image = gr.inputs.Image(shape=(192,192))\n","<ipython-input-15-5c2c720474bc>:1: GradioDeprecationWarning: `optional` parameter is deprecated, and it has no effect\n","  image = gr.inputs.Image(shape=(192,192))\n","<ipython-input-15-5c2c720474bc>:2: GradioDeprecationWarning: Usage of gradio.outputs is deprecated, and will not be supported in the future, please import your components from gradio.components\n","  label = gr.outputs.Label()\n","<ipython-input-15-5c2c720474bc>:2: GradioUnusedKwargWarning: You have unused kwarg parameters in Label, please remove them: {'type': 'auto'}\n","  label = gr.outputs.Label()\n"]},{"name":"stdout","output_type":"stream","text":["Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n","Running on public URL: https://6a9b80fbd65c303307.gradio.live\n","\n","This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"]},{"data":{"text/plain":[]},"execution_count":15,"metadata":{},"output_type":"execute_result"}],"source":["image = gr.inputs.Image(shape=(192,192))\n","label = gr.outputs.Label()\n","examples = [\n","    'test data/viper-2.jpg',\n","    'test data/shutterstock_2062214282-edited-1-scaled.jpg',\n","    'test data/Hornviper_Cerastes_cerastes.jpg',\n","    'test data/download (3).jpg',\n","    'test data/download (4).jpg',\n","    'test data/Bothriechis_schlegelii_(La_Selva_Biological_Station).jpg',\n","    'test data/Naja_sputatrix.jpg',\n","    'test data/download (6).jpg',\n","    'test data/download.jpg'\n","    ]\n","\n","iface = gr.Interface(fn=recognize_snake, inputs=image, outputs=label, examples=examples)\n","iface.launch(inline=False,share=True)"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"jyoS7ruqCLVo"},"outputs":[],"source":["from nbdev.export import notebook2script"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"JIC0S_ebDQcC"},"outputs":[],"source":["notebook2script('app.ipynb')"]}],"metadata":{"colab":{"authorship_tag":"ABX9TyOBRcy8nQYH3eDc0aDhboG7","provenance":[]},"kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.11.4"}},"nbformat":4,"nbformat_minor":0}

app.py

@@ -1,7 +1,49 @@
+from fastai.vision.all import load_learner
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+import pathlib
+temp=pathlib.PosixPath
+pathlib.PosixPath=pathlib.WindowsPath
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+snake_labels = (
+    "Monocled cobra",
+    "Egyptian cobra",
+    "Black-necked spitting cobra",
+    "Samar cobra",
+    "Red spitting cobra",
+    "Javan spitting cobra",
+    "Spectacled cobra",
+    "Russell's viper",
+    "Horned vipers",
+    "Bush vipers",
+    "Eyelash viper",
+    "Saw-scaled vipers",
+    "Banded krait",
+    "Black mamba",
+    "Inland taipan",
+    "Eastern brown snake",
+    "Rattle snake",
+    "King cobra"
+)
+
+model = load_learner('models/snake-recognizer-v0.pkl')
+
+def recognize_snake(photo):
+  pred, idx, probs = model.predict(photo)
+  return dict(zip(snake_labels, map(float, probs)))
+
+
+image = gr.inputs.Image(shape=(192,192))
+label = gr.outputs.Label()
+examples = [
+    'test data/viper-2.jpg',
+    'test data/shutterstock_2062214282-edited-1-scaled.jpg',
+    'test data/download (3).jpg',
+    'test data/download (4).jpg',
+    'test data/Naja_sputatrix.jpg',
+    'test data/download (6).jpg',
+    'test data/download.jpg'
+    ]
+
+iface = gr.Interface(fn=recognize_snake, inputs=image, outputs=label, examples=examples)
+iface.launch(inline=False,share=True)

requirements.txt

@@ -0,0 +1,2 @@
+fastai==2.7.12
+gradio==3.36.1