model, interface, examples added

README.md

@@ -11,3 +11,8 @@ license: mit
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+
+HuggingFace App URL: https://huggingface.co/spaces/ahmedtanvir47/sport-recognizer
+
+Gradio App URL: 

app.ipynb

@@ -0,0 +1,259 @@
+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {
+        "id": "51neqepjqu_z"
+      },
+      "outputs": [],
+      "source": [
+        "#|default_exp app"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "Hm8cO7PDvYZe"
+      },
+      "source": [
+        "# Sports Equipment Recognizer"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "cUZU1ZIavbMD",
+        "outputId": "7ca0248a-0cbd-4dc0-83af-4a5489da5878"
+      },
+      "outputs": [],
+      "source": [
+        "!pip install -Uqq fastai nbdev python-multipart"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 9,
+      "metadata": {
+        "id": "nmylpDsHv3D6"
+      },
+      "outputs": [],
+      "source": [
+        "!pip install -qq gradio==4.44.1\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 4,
+      "metadata": {
+        "id": "FsrcDOg2xzCf"
+      },
+      "outputs": [],
+      "source": [
+        "from fastai.vision.all import *"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 531
+        },
+        "id": "7WvIfcjDvgx9",
+        "outputId": "953a7653-7978-45b7-8d17-ed30b2d7803a"
+      },
+      "outputs": [],
+      "source": [
+        "#!export\n",
+        "from fastai.vision.all import load_learner\n",
+        "import python_multipart\n",
+        "import gradio as gr"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "dSeRJ5RU6j6A"
+      },
+      "outputs": [],
+      "source": [
+        "# from google.colab import drive\n",
+        "# drive.mount('/content/drive')"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "z_uKf6nl6n50"
+      },
+      "outputs": [],
+      "source": [
+        "# %cd /content/drive/My Drive/Sports Equipment"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "euLWl9eAvk-T"
+      },
+      "outputs": [],
+      "source": [
+        "#!export\n",
+        "model = load_learner('models/sport-recognizer-v3.pkl')"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 12,
+      "metadata": {
+        "id": "tzouWGYqwDvF"
+      },
+      "outputs": [],
+      "source": [
+        "#!export\n",
+        "equipment_labels = (\n",
+        "    'Archery Bow',\n",
+        "    'Badminton Shuttlecock',\n",
+        "    'Baseball Bat',\n",
+        "    'Basketball ball',\n",
+        "    'Bowling Ball',\n",
+        "    'Boxing Gloves',\n",
+        "    'Carrom board',\n",
+        "    'Chessboard',\n",
+        "    'Cricket Bat',\n",
+        "    'Frisbee disc',\n",
+        "    'Golf ball',\n",
+        "    'Hockey Stick',\n",
+        "    'Ice Skates',\n",
+        "    'Rugby Ball',\n",
+        "    'Skateboard',\n",
+        "    'Ski Poles',\n",
+        "    'Soccer ball',\n",
+        "    'Table Tennis Paddle',\n",
+        "    'Tennis Racket',\n",
+        "    'Volleyball ball'\n",
+        "\n",
+        ")\n",
+        "\n",
+        "def recognize_image(image):\n",
+        "  pred, idx, probs = model.predict(image)\n",
+        "  return dict(zip(equipment_labels, map(float, probs)))"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "MdysqYkLw5PH"
+      },
+      "outputs": [],
+      "source": [
+        "img = PILImage.create(f'test_images/unknown_01.jpg')\n",
+        "img.thumbnail((192,192))\n",
+        "img"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "yTWEYc-3w82b"
+      },
+      "outputs": [],
+      "source": [
+        "recognize_image(img)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "sXlpu9i8zE5e"
+      },
+      "outputs": [],
+      "source": [
+        "#!export\n",
+        "image = gr.inputs.Image(shape=(192,192))\n",
+        "label = gr.outputs.Label()\n",
+        "examples = [\n",
+        "    'test_images/unknown_00.jpg',\n",
+        "    'test_images/unknown_01.jpg',\n",
+        "    'test_images/unknown_02.jpg',\n",
+        "    'test_images/unknown_03.jpg'\n",
+        "    ]\n",
+        "\n",
+        "iface = gr.Interface(fn=recognize_image, inputs=image, outputs=label, examples=examples)\n",
+        "iface.launch(inline=False)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "3gyUlfJW2jRu"
+      },
+      "source": [
+        "# Notebook to Python Script Export"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "IybJQe222ikO"
+      },
+      "outputs": [],
+      "source": [
+        "from nbdev.export import notebook2script"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "85az32eq3qpJ"
+      },
+      "outputs": [],
+      "source": [
+        "notebook2script('app.ipynb')"
+      ]
+    }
+  ],
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "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": "3.9.13"
+    },
+    "vscode": {
+      "interpreter": {
+        "hash": "f8f14f5a7c49a331ac7a55934b43ce13bd28be1333db14e2d71768ad3378996c"
+      }
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}

app.py

@@ -1,7 +1,53 @@
+from fastai.vision.all import *
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+# import pathlib
+# temp = pathlib.PosixPath
+# pathlib.PosixPath = pathlib.WindowsPath
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+
+
+model = load_learner('models/sport-recognizer-v3.pkl')
+
+equipment_labels = (
+    'Archery Bow',
+    'Badminton Shuttlecock',
+    'Baseball Bat',
+    'Basketball ball',
+    'Bowling Ball',
+    'Boxing Gloves',
+    'Carrom board',
+    'Chessboard',
+    'Cricket Bat',
+    'Frisbee disc',
+    'Golf ball',
+    'Hockey Stick',
+    'Ice Skates',
+    'Rugby Ball',
+    'Skateboard',
+    'Ski Poles',
+    'Soccer ball',
+    'Table Tennis Paddle',
+    'Tennis Racket',
+    'Volleyball ball'
+
+)
+
+def recognize_image(image):
+  pred, idx, probs = model.predict(image)
+  return dict(zip(equipment_labels, map(float, probs)))
+
+
+
+#!export
+image = gr.inputs.Image(shape=(192,192))
+label = gr.outputs.Label()
+examples = [
+    'test_images/unknown_00.jpg',
+    'test_images/unknown_01.jpg',
+    'test_images/unknown_02.jpg',
+    'test_images/unknown_03.jpg'
+    ]
+
+iface = gr.Interface(fn=recognize_image, inputs=image, outputs=label, examples=examples)
+iface.launch(inline=False)

app_old.py

@@ -0,0 +1,7 @@
+import gradio as gr
+
+def greet(name):
+    return "Hello " + name + "!!"
+
+demo = gr.Interface(fn=greet, inputs="text", outputs="text")
+demo.launch()

models/sport-recognizer-v3.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9b02cebf619eac1b1ce182155318ca3461dd1aaf8de283259c04d4741ba414c1
+size 87597196