File size: 69,522 Bytes
d9b4c14
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Hm8cO7PDvYZe"
      },
      "source": [
        "# Obj Recognizer"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "id": "cUZU1ZIavbMD"
      },
      "outputs": [],
      "source": [
        "!pip install -Uqq fastai gradio nbdev"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "FsrcDOg2xzCf"
      },
      "outputs": [],
      "source": [
        "from fastai.vision.all import *"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "7WvIfcjDvgx9"
      },
      "outputs": [],
      "source": [
        "#!export\n",
        "from fastai.vision.all import load_learner\n",
        "import gradio as gr"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dYr2lNrYZ8rP",
        "outputId": "f99dd8b8-6d8c-4f09-8f86-e77f02dfae50"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%cd /content/drive/MyDrive/MasterCourse/CapstonProject02"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dEkeRMa2Z9TX",
        "outputId": "4b620b28-9373-47b3-f5d8-ed200d7927f1"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/drive/MyDrive/MasterCourse/CapstonProject02\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "id": "euLWl9eAvk-T"
      },
      "outputs": [],
      "source": [
        "#!export\n",
        "model = load_learner('models/obj-recognizer-v2.pkl')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "tzouWGYqwDvF"
      },
      "outputs": [],
      "source": [
        "#!export\n",
        "obj_labels = (\n",
        "    \"Cars\",\n",
        "    \"Trucks\",\n",
        "    \"Traffic signals\",\n",
        "    \"Road markings\",\n",
        "    \"Construction zones\",\n",
        "    \"Animals\",\n",
        "    \"Road obstacles\",\n",
        "    \"Pedestrians\",\n",
        "    \"Emergency vehicles\",\n",
        "    \"Bicycles\",\n",
        "    \"Motorcycles\",\n",
        "    \"Buses\",\n",
        "    \"Road works\",\n",
        "    \"Drones\",\n",
        "    \"Zebra crossing\"\n",
        ")\n",
        "\n",
        "def recognize_image(image):\n",
        "  pred, idx, probs = model.predict(image)\n",
        "  return dict(zip(obj_labels, map(float, probs)))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 145
        },
        "id": "MdysqYkLw5PH",
        "outputId": "09cce488-99dd-4854-c852-a34e85cc963e"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "PILImage mode=RGB size=192x128"
            ],
            "image/png": "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\n"
          },
          "metadata": {},
          "execution_count": 9
        }
      ],
      "source": [
        "img = PILImage.create(f'TestImages/Ped.png')\n",
        "img.thumbnail((192,192))\n",
        "img"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 277
        },
        "id": "yTWEYc-3w82b",
        "outputId": "4961d670-0f6a-46c2-eb5a-3a4271b4afd8"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "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"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": []
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'Cars': 8.739420742642778e-09,\n",
              " 'Trucks': 1.0514840909081613e-07,\n",
              " 'Traffic signals': 2.93949344865041e-08,\n",
              " 'Road markings': 8.471176329294394e-07,\n",
              " 'Construction zones': 5.0914868552354164e-06,\n",
              " 'Animals': 6.07438778388314e-07,\n",
              " 'Road obstacles': 5.213905751588754e-07,\n",
              " 'Pedestrians': 1.1889517992358378e-07,\n",
              " 'Emergency vehicles': 0.8648882508277893,\n",
              " 'Bicycles': 3.83423184757703e-06,\n",
              " 'Motorcycles': 1.810474685726149e-07,\n",
              " 'Buses': 9.959463795894408e-07,\n",
              " 'Road works': 5.529435384232784e-06,\n",
              " 'Drones': 9.05185970623279e-08,\n",
              " 'Zebra crossing': 0.13509388267993927}"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ],
      "source": [
        "recognize_image(img)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sXlpu9i8zE5e",
        "outputId": "77ac0b4c-2b13-4363-e884-aa3d0517524f"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/gradio/inputs.py:257: UserWarning: Usage of gradio.inputs is deprecated, and will not be supported in the future, please import your component from gradio.components\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.8/dist-packages/gradio/deprecation.py:40: UserWarning: `optional` parameter is deprecated, and it has no effect\n",
            "  warnings.warn(value)\n",
            "/usr/local/lib/python3.8/dist-packages/gradio/outputs.py:197: UserWarning: Usage of gradio.outputs is deprecated, and will not be supported in the future, please import your components from gradio.components\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.8/dist-packages/gradio/deprecation.py:40: UserWarning: The 'type' parameter has been deprecated. Use the Number component instead.\n",
            "  warnings.warn(value)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n",
            "Note: opening Chrome Inspector may crash demo inside Colab notebooks.\n",
            "\n",
            "To create a public link, set `share=True` in `launch()`.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 11
        }
      ],
      "source": [
        "#!export\n",
        "image = gr.inputs.Image(shape=(192,192))\n",
        "label = gr.outputs.Label()\n",
        "examples = [\n",
        "    'TestImages/Ped.png',\n",
        "    'TestImages/RoadWorks.jpg',\n",
        "    'TestImages/TrafficSignals.jpg',\n",
        "    'TestImages/test.jpg',\n",
        "    'TestImages/trucks.jpg'\n",
        "    ]\n",
        "\n",
        "iface = gr.Interface(fn=recognize_image, inputs=image, outputs=label, examples=examples)\n",
        "iface.launch(inline=False)"
      ]
    }
  ],
  "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 (tags/v3.9.13:6de2ca5, May 17 2022, 16:36:42) [MSC v.1929 64 bit (AMD64)]"
    },
    "vscode": {
      "interpreter": {
        "hash": "f8f14f5a7c49a331ac7a55934b43ce13bd28be1333db14e2d71768ad3378996c"
      }
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}