File size: 2,982 Bytes
a892385
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d2c2b738",
   "metadata": {},
   "outputs": [],
   "source": [
    "from fastai.vision.all import *\n",
    "import gradio as gr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b92d24f3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# search_terms = ('hard hat','construction gloves','safety glasses','construction boots', 'screw driver','hammer','f150')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "34ebdca4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# path = Path('construction_photos')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "04347f65",
   "metadata": {},
   "outputs": [],
   "source": [
    "# dls = DataBlock(\n",
    "#     blocks=(ImageBlock,CategoryBlock),\n",
    "#     getters=None,\n",
    "#     n_inp=None,\n",
    "#     item_tfms=[Resize(224,method='squish')],\n",
    "#     get_items=get_image_files,\n",
    "#     splitter=RandomSplitter(seed=42),\n",
    "#     get_y=parent_label,\n",
    "# ).dataloaders(path,bs=128)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "85098e65",
   "metadata": {},
   "outputs": [],
   "source": [
    "learn = load_learner('construction_things.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "a6ed198b",
   "metadata": {},
   "outputs": [],
   "source": [
    "def classify_image(img):\n",
    "    pred,idx,probs = learn.predict(img)\n",
    "    return dict(zip(dls.vocab,map(float,probs)))\n",
    "# classify_image(get_image_files(path)[100])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b2f582a8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running on local URL:  http://127.0.0.1:7860/\n",
      "\n",
      "To create a public link, set `share=True` in `launch()`.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(<fastapi.applications.FastAPI at 0x7ff6a8761430>,\n",
       " 'http://127.0.0.1:7860/',\n",
       " None)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "image = gr.inputs.Image(shape=(192,192))\n",
    "label = gr.outputs.Label()\n",
    "interface = gr.Interface(fn=classify_image,inputs=image,outputs=label)\n",
    "# interface.launch(inline=True)\n",
    "interface.launch(inline=False)"
   ]
  }
 ],
 "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": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}