feat: main

.ipynb_checkpoints/fineApp-checkpoint.ipynb

@@ -0,0 +1,49 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "ModuleNotFoundError",
+     "evalue": "No module named 'fastbook'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[5], line 3\u001b[0m\n\u001b[1;32m      1\u001b[0m get_ipython()\u001b[39m.\u001b[39msystem(\u001b[39m'\u001b[39m\u001b[39m[ -e /content ] && pip install -Uqq fastbook\u001b[39m\u001b[39m'\u001b[39m)\n\u001b[0;32m----> 3\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39mfastbook\u001b[39;00m\n\u001b[1;32m      4\u001b[0m fastbook\u001b[39m.\u001b[39msetup_book()\n",
+      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'fastbook'"
+     ]
+    }
+   ],
+   "source": [
+    "![ -e /content ] && pip install -Uqq fastbook\n",
+    "\n",
+    "import fastbook\n",
+    "fastbook.setup_book()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "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": "3.10.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

app.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from fastai.vision.all import *\n",
+    "import gradio as gr\n",
+    "\n",
+    "def is_cat(x): return x[0].isupper()\n",
+    "\n",
+    "# Cell\n",
+    "learn = load_learner('model.pkl')\n",
+    "\n",
+    "categories = ('Dog', 'Cat')\n",
+    "\n",
+    "def classify_image(img):\n",
+    "    pred,pred_idx,probs = learn.predict(img)\n",
+    "    return dict(zip(categories, map(float, probs)))\n",
+    "\n",
+    "image = gr.inputs.Image(shape=(192, 192))\n",
+    "label = gr.outputs.Label()\n",
+    "\n",
+    "examples = ['dog.jpg', 'cat.jpg', 'two-dog.jpg']\n",
+    "\n",
+    "intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)\n",
+    "intf.launch(inline=False)\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

app.py

@@ -3,12 +3,10 @@
 from fastai.vision.all import *
 import gradio as gr
 
-def is_cat(x): return x[0].isupper()
-
 # Cell
-learn = load_learner('model.pkl')
+learn = load_learner('pandaBears.pkl')
 
-categories = ('Dog', 'Cat')
+categories = ('Panda', 'Bear')
 
 def classify_image(img):
     pred,pred_idx,probs = learn.predict(img)
@@ -17,7 +15,7 @@ def classify_image(img):
 image = gr.inputs.Image(shape=(192, 192))
 label = gr.outputs.Label()
 
-examples = ['dog.jpg', 'cat.jpg', 'two-dog.jpg']
+examples = ['panda.jpg', 'panda-cartoon.jpg', 'raccoon.jpg', 'bear.jpg']
 
 intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
 intf.launch(inline=False)

cat.jpg → archive.zip

@@ -1,3 +1,3 @@
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-oid sha256:2fcc21f8f005df284a8e31d6128fb11946250d9f019c7542311255ca50d0660f
-size 1058516
+oid sha256:3b1169e14b312c78906ec197085a081c9cdb63ce5d8631645aef9c8f888e1d40
+size 12271601

flagged/log.csv

@@ -0,0 +1,2 @@
+img,output,flag,username,timestamp
+/Users/nazha/nazha-ai/panda-recognizer/flagged/img/tmp4h5dh0a9.jpg,/Users/nazha/nazha-ai/panda-recognizer/flagged/output/tmpu0ljv__f.json,,,2023-07-16 18:40:46.430310

flagged/output/tmpu0ljv__f.json

@@ -0,0 +1 @@
+{"label": "Bear", "confidences": [{"label": "Bear", "confidence": 0.5269274711608887}, {"label": "Panda", "confidence": 0.47307252883911133}]}

dog.jpg → pandaBears.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d53a77b0be82993ed44bbb9244cda42bf460f8dcdf87ff3cfdbfdc7191ff418d
-size 121984
+oid sha256:70a98b7e4e8868b815f8f765be173cbff381085689a02cdbd67aac67f4cc04ee
+size 87466032