"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "collected_data = collected_data[\n",
+ " (\n",
+ " (get_route_points(collected_data) > 1)\n",
+ " | (np.random.random(len(collected_data.index)) < chance_limit)\n",
+ " )\n",
+ "]\n",
+ "get_route_points(collected_data).plot.hist(bins=13)\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 38,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:28.962854Z",
+ "start_time": "2022-07-11T18:34:28.949690Z"
+ }
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "1 174\n",
+ "2 24\n",
+ "3 38\n",
+ "4 113\n",
+ "5 382\n",
+ "6 75\n",
+ "7 125\n",
+ "8 155\n",
+ "9 145\n",
+ "10 157\n",
+ "11 226\n",
+ "12 224\n",
+ "13 200\n",
+ "14 149\n",
+ "15 104\n",
+ "Name: route complexity, dtype: int64"
+ ]
+ },
+ "execution_count": 38,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "get_route_points(collected_data).value_counts().sort_index()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 39,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:29.030033Z",
+ "start_time": "2022-07-11T18:34:28.966774Z"
+ }
+ },
"outputs": [
{
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"
\n",
" \n",
"\n",
- "110745 rows × 6 columns
\n",
+ "2291 rows × 6 columns
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""
],
"text/plain": [
- " obstacles destination_x \\\n",
- "seed \n",
- "0 {'0': POLYGON ((-17.62168766659423 -98.3692662... -66.0 \n",
- "2 {'0': POLYGON ((-46.23706006792075 -76.7569948... 73.0 \n",
- "4 {'0': POLYGON ((-77.97638439917915 -70.2390972... 47.0 \n",
- "5 {'0': POLYGON ((-71.45682729091783 -138.627922... -67.0 \n",
- "6 {'0': POLYGON ((-76.20025009472265 -92.9434076... -67.0 \n",
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- "133447 {'0': POLYGON ((-15.11578684131388 -83.2968281... 60.0 \n",
- "133448 {'0': POLYGON ((-40.190401796991324 -82.393980... 40.0 \n",
- "133449 {'0': POLYGON ((-36.69132405456605 -97.9877273... -30.0 \n",
- "\n",
- " destination_y image \\\n",
- "seed \n",
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- "133447 -27.0 \n",
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- "133449 -66.0 \n",
- "\n",
- " route cost \n",
+ " obstacles destination_x \\\n",
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- "133449 [[0.0, 0.0], [-2.7740483244056953, -6.60226117... 120.022162 \n",
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"\n",
- "[110745 rows x 6 columns]"
+ " destination_y image route \\\n",
+ "seed \n",
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]
},
- "execution_count": 28,
+ "execution_count": 39,
"metadata": {},
"output_type": "execute_result"
}
@@ -2052,113 +2169,1269 @@
},
{
"cell_type": "code",
- "execution_count": 29,
- "metadata": {},
+ "execution_count": 40,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:29.039493Z",
+ "start_time": "2022-07-11T18:34:29.033596Z"
+ }
+ },
"outputs": [],
"source": [
- "def generate_image_maps(row):\n",
- " return (\n",
- " generate_image_from_map(\n",
- " obstacles=row.obstacles,\n",
- " destination=Point(row.destination_x, row.destination_y),\n",
- " route=row.route,\n",
- " route_type=\"dot\",\n",
- " ),\n",
- " generate_image_from_map(\n",
- " obstacles=row.obstacles,\n",
- " destination=Point(row.destination_x, row.destination_y),\n",
- " route=row.route,\n",
- " route_type=\"line\",\n",
- " ),\n",
- " )"
+ "del chance_limit"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Memory consumption"
]
},
{
"cell_type": "code",
- "execution_count": 30,
- "metadata": {},
+ "execution_count": 41,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:29.105061Z",
+ "start_time": "2022-07-11T18:34:29.043526Z"
+ }
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
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+ " \n",
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+ " | \n",
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+ " destination_y | \n",
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\n",
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+ "text/plain": [
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+ "\n",
+ "[2291 rows x 6 columns]"
+ ]
+ },
+ "execution_count": 41,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "collected_data"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 42,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:29.149676Z",
+ "start_time": "2022-07-11T18:34:29.111848Z"
+ }
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'246.8 kB'"
+ ]
+ },
+ "execution_count": 42,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "import humanize\n",
+ "import sys\n",
+ "\n",
+ "\n",
+ "def generate_image_maps(row, route_type: Literal[\"dot\", \"line\"]):\n",
+ " img = np.expand_dims(\n",
+ " np.asarray(\n",
+ " generate_image_from_map(\n",
+ " obstacles=row.obstacles,\n",
+ " destination=Point(row.destination_x, row.destination_y),\n",
+ " route=row.route,\n",
+ " route_type=route_type,\n",
+ " seed=row.name,\n",
+ " )\n",
+ " ),\n",
+ " axis=0,\n",
+ " )\n",
+ " img = img // 0xFF\n",
+ " return img\n",
+ "\n",
+ "\n",
+ "generated = collected_data.head().apply(generate_image_maps, axis=1, args=(\"dot\",))\n",
+ "humanize.naturalsize(generated.memory_usage(deep=True))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 43,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:29.160218Z",
+ "start_time": "2022-07-11T18:34:29.154190Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "if \"image\" in collected_data.columns:\n",
+ " del collected_data[\"image\"]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 44,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:30.030972Z",
+ "start_time": "2022-07-11T18:34:29.164607Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "DATA_WITH_IMG_PATH: Final[str] = \"data/collected_and_filtered.pickle\"\n",
+ "if os.path.exists(DATA_WITH_IMG_PATH) and not GENERATE_NEW:\n",
+ " collected_data = pd.read_pickle(DATA_WITH_IMG_PATH)\n",
+ "else:\n",
+ " collected_data.to_pickle(DATA_WITH_IMG_PATH)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 45,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:35.027458Z",
+ "start_time": "2022-07-11T18:34:30.033852Z"
+ }
+ },
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
- "model_id": "c48fbc156301459ea6bd45ba18c0dbb2",
+ "model_id": "2714b97790dd4acabec798c503b007a1",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
- " 0%| | 0/72 [00:00, ?it/s]"
+ " 0%| | 0/2291 [00:00, ?it/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "image_series = collected_data.progress_apply(\n",
+ " generate_image_maps, axis=1, args=(\"line\",)\n",
+ ")\n",
+ "\n",
+ "# collected_data[\"image_lines\"] = collected_data.apply(\n",
+ "# generate_image_maps, axis=1, args=(\"line\",)\n",
+ "# )"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 46,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:35.085664Z",
+ "start_time": "2022-07-11T18:34:35.032718Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "collected_routes = np.concatenate(image_series)\n",
+ "del image_series"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 47,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:35.095020Z",
+ "start_time": "2022-07-11T18:34:35.088433Z"
+ }
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'112.6 MB'"
+ ]
+ },
+ "execution_count": 47,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "humanize.naturalsize(sys.getsizeof(collected_routes))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 48,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:35.107314Z",
+ "start_time": "2022-07-11T18:34:35.099032Z"
+ }
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "dtype('uint8')"
+ ]
+ },
+ "execution_count": 48,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "collected_routes.dtype"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 49,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:35.124351Z",
+ "start_time": "2022-07-11T18:34:35.111145Z"
+ }
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "{'collected_routes': '112.6 MB',\n",
+ " 'collected_data': '2.8 MB',\n",
+ " 'route_points': '276.0 kB',\n",
+ " 'generated': '246.9 kB',\n",
+ " 'row': '2.0 kB',\n",
+ " 'CartesianRoute': '1.1 kB',\n",
+ " 'LineString': '1.1 kB',\n",
+ " 'Point': '1.1 kB',\n",
+ " 'TimingFrame': '1.1 kB',\n",
+ " 'Polygon': '904 Bytes'}"
+ ]
+ },
+ "execution_count": 49,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "memory = sorted(\n",
+ " [\n",
+ " (x, sys.getsizeof(globals().get(x)))\n",
+ " for x in dir()\n",
+ " if not x.startswith(\"_\") and x not in sys.modules\n",
+ " ],\n",
+ " key=lambda x: x[1],\n",
+ " reverse=True,\n",
+ ")\n",
+ "memory = {name: humanize.naturalsize(mem) for name, mem in memory[:10]}\n",
+ "memory"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 50,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:35.811285Z",
+ "start_time": "2022-07-11T18:34:35.128881Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "COLLECTED_ROUTES_DUMP = \"data/collected_routes_np.pickle\"\n",
+ "with open(COLLECTED_ROUTES_DUMP, \"wb\") as f:\n",
+ " pickle.dump(collected_routes, f)\n",
+ "\n",
+ "# with open(COLLECTED_ROUTES_DUMP,'rb') as f: collected_routes = pickle.load(f)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "[Pix2Pix Tensorflow](https://www.tensorflow.org/tutorials/generative/pix2pix)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 51,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:35.846820Z",
+ "start_time": "2022-07-11T18:34:35.815078Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "2022-07-11 18:34:35.822076: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory\n",
+ "2022-07-11 18:34:35.822130: W tensorflow/stream_executor/cuda/cuda_driver.cc:269] failed call to cuInit: UNKNOWN ERROR (303)\n",
+ "2022-07-11 18:34:35.822152: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (f874d07da7f2): /proc/driver/nvidia/version does not exist\n",
+ "2022-07-11 18:34:35.822569: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA\n",
+ "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 51,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Source: https://www.tensorflow.org/tutorials/generative/pix2pix\n",
+ "def downsample(filters, size, apply_batchnorm=True):\n",
+ " initializer = tf.random_normal_initializer(mean=0.0, stddev=0.02)\n",
+ "\n",
+ " result = tf.keras.Sequential()\n",
+ " result.add(\n",
+ " tf.keras.layers.Conv2D(\n",
+ " filters,\n",
+ " size,\n",
+ " strides=2,\n",
+ " padding=\"same\",\n",
+ " kernel_initializer=initializer,\n",
+ " use_bias=False,\n",
+ " )\n",
+ " )\n",
+ "\n",
+ " if apply_batchnorm:\n",
+ " result.add(tf.keras.layers.BatchNormalization())\n",
+ "\n",
+ " result.add(tf.keras.layers.LeakyReLU())\n",
+ "\n",
+ " return result\n",
+ "\n",
+ "\n",
+ "downsample(64, 4)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 52,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:35.859119Z",
+ "start_time": "2022-07-11T18:34:35.852272Z"
+ }
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(128, 128, 3)"
+ ]
+ },
+ "execution_count": 52,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "collected_routes[0].shape"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 53,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:35.873070Z",
+ "start_time": "2022-07-11T18:34:35.862530Z"
+ }
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "TensorShape([1, 128, 128, 3])"
+ ]
+ },
+ "execution_count": 53,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "tf.expand_dims(collected_routes[0], 0).shape"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 54,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:35.948246Z",
+ "start_time": "2022-07-11T18:34:35.877228Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "(1, 64, 64, 3)\n"
+ ]
+ }
+ ],
+ "source": [
+ "down_model = downsample(3, 4)\n",
+ "tf.cast(tf.expand_dims(collected_routes[1], 0), \"float16\", name=None)\n",
+ "\n",
+ "down_result = down_model(\n",
+ " tf.cast(tf.expand_dims(collected_routes[1], 0), \"float16\", name=None)\n",
+ ")\n",
+ "print(down_result.shape)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 55,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:35.959098Z",
+ "start_time": "2022-07-11T18:34:35.953165Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "# Source: https://www.tensorflow.org/tutorials/generative/pix2pix\n",
+ "def upsample(filters, size, apply_dropout=False):\n",
+ " initializer = tf.random_normal_initializer(0.0, 0.02)\n",
+ "\n",
+ " result = tf.keras.Sequential()\n",
+ " result.add(\n",
+ " tf.keras.layers.Conv2DTranspose(\n",
+ " filters,\n",
+ " size,\n",
+ " strides=2,\n",
+ " padding=\"same\",\n",
+ " kernel_initializer=initializer,\n",
+ " use_bias=False,\n",
+ " )\n",
+ " )\n",
+ "\n",
+ " result.add(tf.keras.layers.BatchNormalization())\n",
+ "\n",
+ " if apply_dropout:\n",
+ " result.add(tf.keras.layers.Dropout(0.5))\n",
+ "\n",
+ " result.add(tf.keras.layers.ReLU())\n",
+ "\n",
+ " return result"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 56,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:36.012492Z",
+ "start_time": "2022-07-11T18:34:35.963668Z"
+ }
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "TensorShape([1, 128, 128, 3])"
+ ]
+ },
+ "execution_count": 56,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "up_model = upsample(3, 4)\n",
+ "up_result = up_model(down_result)\n",
+ "up_result.shape"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 57,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:36.888819Z",
+ "start_time": "2022-07-11T18:34:36.015415Z"
+ }
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 57,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "def Generator():\n",
+ " OUTPUT_CHANNELS: Final[int] = 1\n",
+ " inputs = tf.keras.layers.Input(shape=[IMG_SIZE, IMG_SIZE, 2])\n",
+ "\n",
+ " down_stack = [\n",
+ " downsample(64, 4, apply_batchnorm=False), # (batch_size, 64, 64, 128)\n",
+ " downsample(128, 4), # (batch_size, 8, 8, 512)\n",
+ " downsample(512, 4), # (batch_size, 4, 4, 512)\n",
+ " downsample(512, 4), # (batch_size, 2, 2, 512)\n",
+ " downsample(512, 4), # (batch_size, 1, 1, 512)\n",
+ " downsample(512, 4), # (batch_size, 1, 1, 512)\n",
+ " downsample(512, 4), # (batch_size, 1, 1, 512)\n",
+ " ]\n",
+ "\n",
+ " up_stack = [\n",
+ " upsample(512, 4, apply_dropout=True), # (batch_size, 4, 4, 1024)\n",
+ " upsample(512, 4, apply_dropout=True), # (batch_size, 4, 4, 1024)\n",
+ " upsample(512, 4, apply_dropout=True), # (batch_size, 4, 4, 1024)\n",
+ " upsample(512, 4), # (batch_size, 16, 16, 1024)\n",
+ " upsample(128, 4), # (batch_size, 32, 32, 512)\n",
+ " upsample(64, 4), # (batch_size, 64, 64, 256)\n",
+ " ]\n",
+ "\n",
+ " initializer = tf.random_normal_initializer(0.0, 0.02)\n",
+ " last = tf.keras.layers.Conv2DTranspose(\n",
+ " OUTPUT_CHANNELS,\n",
+ " 4,\n",
+ " strides=2,\n",
+ " padding=\"same\",\n",
+ " kernel_initializer=initializer,\n",
+ " activation=\"tanh\",\n",
+ " ) # (batch_size, 256, 256, 3)\n",
+ "\n",
+ " x = inputs\n",
+ "\n",
+ " # Downsampling through the model\n",
+ " skips = []\n",
+ " for down in down_stack:\n",
+ " x = down(x)\n",
+ " skips.append(x)\n",
+ "\n",
+ " skips = reversed(skips[:-1])\n",
+ "\n",
+ " # Upsampling and establishing the skip connections\n",
+ " for up, skip in zip(up_stack, skips):\n",
+ " x = up(x)\n",
+ " x = tf.keras.layers.Concatenate()([x, skip])\n",
+ "\n",
+ " x = last(x)\n",
+ "\n",
+ " return tf.keras.Model(inputs=inputs, outputs=x)\n",
+ "\n",
+ "\n",
+ "generator = Generator()\n",
+ "tf.keras.utils.plot_model(generator, show_shapes=True, dpi=64)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 58,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:36.909543Z",
+ "start_time": "2022-07-11T18:34:36.893252Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "generator.compile(\n",
+ " optimizer=tf.keras.optimizers.RMSprop(), # Optimizer\n",
+ " # Loss function to minimize\n",
+ " loss=\"binary_crossentropy\",\n",
+ " # tf.keras.losses.SparseCategoricalCrossentropy(),\n",
+ " # List of metrics to monitor\n",
+ " metrics=[\n",
+ " \"binary_crossentropy\",\n",
+ " \"mean_squared_error\",\n",
+ " \"mean_absolute_error\",\n",
+ " ], # root_mean_squared_error\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 59,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:36.922590Z",
+ "start_time": "2022-07-11T18:34:36.913165Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "2022-07-11 18:34:36.917085: I tensorflow/core/profiler/lib/profiler_session.cc:99] Profiler session initializing.\n",
+ "2022-07-11 18:34:36.917167: I tensorflow/core/profiler/lib/profiler_session.cc:114] Profiler session started.\n",
+ "2022-07-11 18:34:36.918650: I tensorflow/core/profiler/lib/profiler_session.cc:126] Profiler session tear down.\n"
+ ]
+ }
+ ],
+ "source": [
+ "tqdm_callback = tfa.callbacks.TQDMProgressBar(\n",
+ " leave_epoch_progress=False, leave_overall_progress=True, show_epoch_progress=True\n",
+ ")\n",
+ "\n",
+ "early_stop = tf.keras.callbacks.EarlyStopping(\n",
+ " monitor=\"some metric\",\n",
+ " min_delta=0.0001,\n",
+ " patience=5,\n",
+ " verbose=0,\n",
+ " mode=\"auto\",\n",
+ " restore_best_weights=True,\n",
+ ")\n",
+ "\n",
+ "tf_board = tf.keras.callbacks.TensorBoard(\n",
+ " log_dir=\"./log_dir\",\n",
+ " histogram_freq=100,\n",
+ " write_graph=False,\n",
+ " write_images=False,\n",
+ " write_steps_per_second=True,\n",
+ " update_freq=\"epoch\",\n",
+ " profile_batch=(20, 40),\n",
+ " embeddings_freq=0,\n",
+ " embeddings_metadata=None,\n",
+ ")\n",
+ "\n",
+ "reduce_learing_rate = tf.keras.callbacks.ReduceLROnPlateau(\n",
+ " monitor=\"some metric\", factor=0.2, patience=5, min_lr=000.1, verbose=1\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 60,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:37.387799Z",
+ "start_time": "2022-07-11T18:34:36.925978Z"
+ }
+ },
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "7d2ac0fb253a4cdb9912c39538f2b0d4",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ " 0%| | 0/3 [00:00, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
- "ename": "IndexError",
- "evalue": "image index out of range",
- "output_type": "error",
- "traceback": [
- "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
- "\u001b[0;31mRemoteTraceback\u001b[0m Traceback (most recent call last)",
- "\u001b[0;31mRemoteTraceback\u001b[0m: \n\"\"\"\nTraceback (most recent call last):\n File \"/usr/local/lib/python3.10/dist-packages/multiprocess/pool.py\", line 125, in worker\n result = (True, func(*args, **kwds))\n File \"/usr/local/lib/python3.10/dist-packages/pathos/helpers/mp_helper.py\", line -1, in \n File \"/usr/local/lib/python3.10/dist-packages/mapply/mapply.py\", line 231, in run_apply\n File \"/usr/local/lib/python3.10/dist-packages/pandas/core/frame.py\", line 8845, in apply\n return op.apply().__finalize__(self, method=\"apply\")\n File \"/usr/local/lib/python3.10/dist-packages/pandas/core/apply.py\", line 733, in apply\n return self.apply_standard()\n File \"/usr/local/lib/python3.10/dist-packages/pandas/core/apply.py\", line 857, in apply_standard\n results, res_index = self.apply_series_generator()\n File \"/usr/local/lib/python3.10/dist-packages/pandas/core/apply.py\", line 873, in apply_series_generator\n results[i] = self.f(v)\n File \"/tmp/ipykernel_21416/2110571306.py\", line 5, in generate_image_maps\n generate_image_from_map(\n File \"/tmp/ipykernel_21416/3792534904.py\", line 37, in generate_image_from_map\n img.putpixel(point, (0, 0, 0xFF))\n File \"/usr/local/lib/python3.10/dist-packages/PIL/Image.py\", line 1868, in putpixel\n return self.im.putpixel(xy, value)\nIndexError: image index out of range\n\"\"\"",
- "\nThe above exception was the direct cause of the following exception:\n",
- "\u001b[0;31mIndexError\u001b[0m Traceback (most recent call last)",
- "Input \u001b[0;32mIn [30]\u001b[0m, in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0m collected_data[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mimage_points\u001b[39m\u001b[38;5;124m\"\u001b[39m], collected_data[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mimage_lines\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[43mcollected_data\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmapply\u001b[49m\u001b[43m(\u001b[49m\u001b[43mgenerate_image_maps\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2\u001b[0m collected_data\n",
- "File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/mapply/mapply.py:110\u001b[0m, in \u001b[0;36mmapply\u001b[0;34m(df_or_series, func, axis, n_workers, chunk_size, max_chunks_per_worker, progressbar, args, **kwargs)\u001b[0m\n\u001b[1;32m 107\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m isseries:\n\u001b[1;32m 108\u001b[0m kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124maxis\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m axis\n\u001b[0;32m--> 110\u001b[0m results \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mlist\u001b[39;49m\u001b[43m(\u001b[49m\n\u001b[1;32m 111\u001b[0m \u001b[43m \u001b[49m\u001b[43mmultiprocessing_imap\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 112\u001b[0m \u001b[43m \u001b[49m\u001b[43mpartial\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrun_apply\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 113\u001b[0m \u001b[43m \u001b[49m\u001b[43mdfs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 114\u001b[0m \u001b[43m \u001b[49m\u001b[43mn_workers\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mn_workers\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 115\u001b[0m \u001b[43m \u001b[49m\u001b[43mprogressbar\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mprogressbar\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 116\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 117\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 119\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m (\n\u001b[1;32m 120\u001b[0m isseries\n\u001b[1;32m 121\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(results) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m 122\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(results[\u001b[38;5;241m0\u001b[39m]) \u001b[38;5;241m*\u001b[39m \u001b[38;5;28mlen\u001b[39m(results) \u001b[38;5;129;01min\u001b[39;00m df_or_series\u001b[38;5;241m.\u001b[39mshape\n\u001b[1;32m 123\u001b[0m ):\n\u001b[1;32m 124\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m concat(results, copy\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n",
- "File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/mapply/parallel.py:105\u001b[0m, in \u001b[0;36mmultiprocessing_imap\u001b[0;34m(func, iterable, n_workers, progressbar, args, **kwargs)\u001b[0m\n\u001b[1;32m 102\u001b[0m stage \u001b[38;5;241m=\u001b[39m tqdm(stage, total\u001b[38;5;241m=\u001b[39mn_chunks)\n\u001b[1;32m 104\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 105\u001b[0m \u001b[38;5;28;01myield from\u001b[39;00m stage\n\u001b[1;32m 106\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m (\u001b[38;5;167;01mException\u001b[39;00m, \u001b[38;5;167;01mKeyboardInterrupt\u001b[39;00m):\n\u001b[1;32m 107\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m pool:\n",
- "File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/tqdm/notebook.py:258\u001b[0m, in \u001b[0;36mtqdm_notebook.__iter__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 256\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 257\u001b[0m it \u001b[38;5;241m=\u001b[39m \u001b[38;5;28msuper\u001b[39m(tqdm_notebook, \u001b[38;5;28mself\u001b[39m)\u001b[38;5;241m.\u001b[39m\u001b[38;5;21m__iter__\u001b[39m()\n\u001b[0;32m--> 258\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m obj \u001b[38;5;129;01min\u001b[39;00m it:\n\u001b[1;32m 259\u001b[0m \u001b[38;5;66;03m# return super(tqdm...) will not catch exception\u001b[39;00m\n\u001b[1;32m 260\u001b[0m \u001b[38;5;28;01myield\u001b[39;00m obj\n\u001b[1;32m 261\u001b[0m \u001b[38;5;66;03m# NB: except ... [ as ...] breaks IPython async KeyboardInterrupt\u001b[39;00m\n",
- "File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/tqdm/std.py:1195\u001b[0m, in \u001b[0;36mtqdm.__iter__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1192\u001b[0m time \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_time\n\u001b[1;32m 1194\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 1195\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m obj \u001b[38;5;129;01min\u001b[39;00m iterable:\n\u001b[1;32m 1196\u001b[0m \u001b[38;5;28;01myield\u001b[39;00m obj\n\u001b[1;32m 1197\u001b[0m \u001b[38;5;66;03m# Update and possibly print the progressbar.\u001b[39;00m\n\u001b[1;32m 1198\u001b[0m \u001b[38;5;66;03m# Note: does not call self.update(1) for speed optimisation.\u001b[39;00m\n",
- "File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/multiprocess/pool.py:870\u001b[0m, in \u001b[0;36mIMapIterator.next\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m 868\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m success:\n\u001b[1;32m 869\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m value\n\u001b[0;32m--> 870\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m value\n",
- "\u001b[0;31mIndexError\u001b[0m: image index out of range"
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plt.figure(figsize=(17.5, 25))\n",
+ "np_array = np.flip(collected_routes[1, :, :, :], axis=0)\n",
+ "\n",
+ "for chanel in tqdm(range(3)):\n",
+ " plt.subplot(1, 4, chanel + 1)\n",
+ " plt.imshow(np_array[:, :, chanel], interpolation=\"nearest\")\n",
+ "plt.subplot(1, 4, 4)\n",
+ "plt.imshow(0x88 * np_array[:, :, 0] + 0xFF * np_array[:, :, 2], interpolation=\"nearest\")\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 61,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:37.398038Z",
+ "start_time": "2022-07-11T18:34:37.391964Z"
+ }
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(2291, 128, 128, 2)"
+ ]
+ },
+ "execution_count": 61,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "collected_routes[:, :, :, :2].shape"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 62,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:37.769969Z",
+ "start_time": "2022-07-11T18:34:37.402840Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "train_dataset = tf.data.Dataset.from_tensor_slices(\n",
+ " (collected_routes[:, :, :, :2], collected_routes[:, :, :, 2])\n",
+ ")\n",
+ "# test_dataset = tf.data.Dataset.from_tensor_slices((test_examples, test_labels))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 63,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:37.780494Z",
+ "start_time": "2022-07-11T18:34:37.772901Z"
+ }
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 63,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "train_dataset"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 64,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:37.789908Z",
+ "start_time": "2022-07-11T18:34:37.784588Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "BATCH_SIZE = 64\n",
+ "SHUFFLE_BUFFER_SIZE = 100\n",
+ "# train_dataset = train_dataset.shuffle(SHUFFLE_BUFFER_SIZE).batch(BATCH_SIZE)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 65,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T18:34:37.800259Z",
+ "start_time": "2022-07-11T18:34:37.794044Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "train_dataset = train_dataset.batch(BATCH_SIZE)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 66,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T20:34:10.831132Z",
+ "start_time": "2022-07-11T18:34:37.804670Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Epoch 1/20\n",
+ "36/36 [==============================] - 375s 10s/step - loss: 0.0132 - binary_crossentropy: 0.0132 - mean_squared_error: 0.1258 - mean_absolute_error: 0.2735\n",
+ "Epoch 2/20\n",
+ "36/36 [==============================] - 375s 10s/step - loss: 0.0070 - binary_crossentropy: 0.0070 - mean_squared_error: 0.1279 - mean_absolute_error: 0.2783\n",
+ "Epoch 3/20\n",
+ "36/36 [==============================] - 369s 10s/step - loss: 0.0070 - binary_crossentropy: 0.0070 - mean_squared_error: 0.1281 - mean_absolute_error: 0.2795\n",
+ "Epoch 4/20\n",
+ "36/36 [==============================] - 362s 10s/step - loss: 0.0070 - binary_crossentropy: 0.0070 - mean_squared_error: 0.1284 - mean_absolute_error: 0.2806\n",
+ "Epoch 5/20\n",
+ "36/36 [==============================] - 359s 10s/step - loss: 0.0070 - binary_crossentropy: 0.0070 - mean_squared_error: 0.1290 - mean_absolute_error: 0.2822\n",
+ "Epoch 6/20\n",
+ "36/36 [==============================] - 354s 10s/step - loss: 0.0070 - binary_crossentropy: 0.0070 - mean_squared_error: 0.1293 - mean_absolute_error: 0.2830\n",
+ "Epoch 7/20\n",
+ "36/36 [==============================] - 357s 10s/step - loss: 0.0070 - binary_crossentropy: 0.0070 - mean_squared_error: 0.1305 - mean_absolute_error: 0.2850\n",
+ "Epoch 8/20\n",
+ "36/36 [==============================] - 354s 10s/step - loss: 0.0070 - binary_crossentropy: 0.0070 - mean_squared_error: 0.1318 - mean_absolute_error: 0.2873\n",
+ "Epoch 9/20\n",
+ "36/36 [==============================] - 354s 10s/step - loss: 0.0070 - binary_crossentropy: 0.0070 - mean_squared_error: 0.1318 - mean_absolute_error: 0.2873\n",
+ "Epoch 10/20\n",
+ "36/36 [==============================] - 354s 10s/step - loss: 0.0070 - binary_crossentropy: 0.0070 - mean_squared_error: 0.1318 - mean_absolute_error: 0.2873\n",
+ "Epoch 11/20\n",
+ "36/36 [==============================] - 356s 10s/step - loss: 0.0070 - binary_crossentropy: 0.0070 - mean_squared_error: 0.1395 - mean_absolute_error: 0.3011\n",
+ "Epoch 12/20\n",
+ "36/36 [==============================] - 357s 10s/step - loss: 0.0070 - binary_crossentropy: 0.0070 - mean_squared_error: 0.1414 - mean_absolute_error: 0.3044\n",
+ "Epoch 13/20\n",
+ "36/36 [==============================] - 353s 10s/step - loss: 0.0070 - binary_crossentropy: 0.0070 - mean_squared_error: 0.1414 - mean_absolute_error: 0.3044\n",
+ "Epoch 14/20\n",
+ "36/36 [==============================] - 354s 10s/step - loss: 0.0070 - binary_crossentropy: 0.0070 - mean_squared_error: 0.1414 - mean_absolute_error: 0.3045\n",
+ "Epoch 15/20\n",
+ "36/36 [==============================] - 357s 10s/step - loss: 0.0070 - binary_crossentropy: 0.0070 - mean_squared_error: 0.1414 - mean_absolute_error: 0.3044\n",
+ "Epoch 16/20\n",
+ "36/36 [==============================] - 357s 10s/step - loss: 0.0070 - binary_crossentropy: 0.0070 - mean_squared_error: 0.1414 - mean_absolute_error: 0.3044\n",
+ "Epoch 17/20\n",
+ "36/36 [==============================] - 355s 10s/step - loss: 0.0070 - binary_crossentropy: 0.0070 - mean_squared_error: 0.1414 - mean_absolute_error: 0.3044\n",
+ "Epoch 18/20\n",
+ "36/36 [==============================] - 355s 10s/step - loss: 0.0070 - binary_crossentropy: 0.0070 - mean_squared_error: 0.1414 - mean_absolute_error: 0.3045\n",
+ "Epoch 19/20\n",
+ "36/36 [==============================] - 355s 10s/step - loss: 0.0070 - binary_crossentropy: 0.0070 - mean_squared_error: 0.1414 - mean_absolute_error: 0.3044\n",
+ "Epoch 20/20\n",
+ "36/36 [==============================] - 362s 10s/step - loss: 0.0070 - binary_crossentropy: 0.0070 - mean_squared_error: 0.1414 - mean_absolute_error: 0.3044\n"
]
}
],
"source": [
- "collected_data[\"image_points\"], collected_data[\"image_lines\"] = collected_data.mapply(\n",
- " generate_image_maps, axis=1\n",
- ")\n",
- "collected_data"
+ "history = generator.fit(\n",
+ " train_dataset,\n",
+ " epochs=20,\n",
+ " batch_size=128,\n",
+ " use_multiprocessing=True,\n",
+ " # callbacks=[tqdm_callback, early_stop, tf_board], validation_split=0.20, shuffle=True,\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 69,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T20:35:09.893719Z",
+ "start_time": "2022-07-11T20:35:09.785795Z"
+ }
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[]"
+ ]
+ },
+ "execution_count": 69,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": "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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plt.plot(history.history[\"loss\"])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 74,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T20:36:41.233512Z",
+ "start_time": "2022-07-11T20:36:41.228150Z"
+ }
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(1, 128, 128, 2)"
+ ]
+ },
+ "execution_count": 74,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "collected_routes[0:1, :, :, :2].shape"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 81,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T20:40:42.106870Z",
+ "start_time": "2022-07-11T20:38:39.288499Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "72/72 [==============================] - 122s 2s/step\n"
+ ]
+ }
+ ],
+ "source": [
+ "predicted = generator.predict(\n",
+ " collected_routes[:, :, :, :2],\n",
+ " batch_size=None,\n",
+ " verbose=\"auto\",\n",
+ " steps=None,\n",
+ " callbacks=None,\n",
+ " max_queue_size=10,\n",
+ " workers=1,\n",
+ " use_multiprocessing=False,\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 83,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T20:40:42.284261Z",
+ "start_time": "2022-07-11T20:40:42.275481Z"
+ }
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(2291, 128, 128, 1)"
+ ]
+ },
+ "execution_count": 83,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "predicted.shape"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 84,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T20:40:42.419205Z",
+ "start_time": "2022-07-11T20:40:42.290807Z"
+ }
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 84,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plt.imshow(predicted[0, :, :, 0], interpolation=\"nearest\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 82,
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T20:40:42.270774Z",
+ "start_time": "2022-07-11T20:40:42.111264Z"
+ }
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 82,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": "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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plt.imshow(collected_routes[0, :, :, 0], interpolation=\"nearest\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
- "pycharm": {
- "is_executing": true,
- "name": "#%%\n"
+ "ExecuteTime": {
+ "end_time": "2022-07-11T20:34:11.274201Z",
+ "start_time": "2022-07-11T20:34:11.274188Z"
}
},
"outputs": [],
"source": [
- "DATA_WITH_IMG_PATH: Final[str] = \"data/collectedWithImage.pickle\"\n",
- "\n",
- "\n",
- "def generate_image_maps(row):\n",
- " return generate_image_from_map(\n",
- " obstacles=row.obstacles,\n",
- " destination=Point(row.destination_x, row.destination_y),\n",
- " route=row.route,\n",
- " )\n",
- "\n",
- "\n",
- "if os.path.exists(DATA_WITH_IMG_PATH):\n",
- " collected_data = pd.read_pickle(DATA_WITH_IMG_PATH)\n",
- "else:\n",
- " (\n",
- " collected_data[\"image_points\"],\n",
- " collected_data[\"image_lines\"],\n",
- " ) = collected_data.mapply(generate_image_maps, axis=1)\n",
- " del collected_data[\"image\"]\n",
- " collected_data.to_pickle(DATA_WITH_IMG_PATH)"
+ "# tf.keras.utils.plot_model(generator)"
]
},
{
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
+ "cell_type": "raw",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2022-07-11T16:47:19.020872Z",
+ "start_time": "2022-07-11T16:47:17.607427Z"
+ }
+ },
"source": [
- "# pd.Series([1,2,3,4,5,6]).apply()"
+ "!pip install pydot pydotplus graphviz"
]
},
{
@@ -2171,53 +3444,6 @@
"source": [
"Ich würde auch zu 1. tendieren, stimme Ihnen aber zu, dass das Thema sehr umfangreich ist. Könnte man sich nicht einen Teilbereich herauspicken? Ich verstehe nicht viel vom Segeln, daher lassen Sie mich kurz zusammenfassen, was Sie vorhaben: - Sie generieren Trainingsdaten mit dem existierenden aber langsamen GD Algorithmus. Ich nehme an, es handelt sich um lokale Routen in einem relativ kleinen Kartenausschnitt. Lässt es die Laufzeit zu, dass Sie eine große Menge an Routen berechnen. - Sie haben dann eine Karte und als Ausgabe eine Liste der Wendepunkte - Warum wollen Sie daraus eine Heatmap berechnen? Diesen Schritt habe ich noch nicht verstanden - Wenn Sie aus einer Karte eine Heatmap trainieren wollen und dafür genügend Beispiele haben, könnnten GANs hilfreich sein: https://arxiv.org/abs/1611.07004 Ich würde Ihnen raten, das Problem möglichst so zu reduzieren, dass es im Rahmen des Moduls noch handhabbar bleibt. Alles Weitere kann man sich auch für spätere Arbeiten aufbewahren. Das 2. Thema ist auch ok. Aber vielleicht nicht ganz so spannend. Ich überlasse Ihnen die Entscheidung. Freundliche Grüße Heiner Giefers"
]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "import matplotlib\n",
- "import numpy as np\n",
- "import matplotlib.pyplot as plt"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "xs = np.linspace(-1, 1)\n",
- "plt.subplot(2, 2, 1)\n",
- "plt.plot(xs, np.sin(xs))\n",
- "plt.subplot(2, 2, 2)\n",
- "plt.plot(xs, np.cos(xs))\n",
- "plt.subplot(2, 2, 3)\n",
- "plt.plot(xs, np.tan(xs))\n",
- "plt.subplot(2, 2, 4)\n",
- "plt.show()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "f, ax = plt.subplots(figsize=(5, 5))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "# better next time\n",
- "Min distance zwischen ziel und hindernis einfügen"
- ]
}
],
"metadata": {
@@ -2237,6 +3463,19 @@
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.4"
+ },
+ "toc": {
+ "base_numbering": 1,
+ "nav_menu": {},
+ "number_sections": true,
+ "sideBar": true,
+ "skip_h1_title": false,
+ "title_cell": "Table of Contents",
+ "title_sidebar": "Contents",
+ "toc_cell": false,
+ "toc_position": {},
+ "toc_section_display": true,
+ "toc_window_display": false
}
},
"nbformat": 4,
diff --git a/pyrate b/pyrate
index d44f308..814b6dd 160000
--- a/pyrate
+++ b/pyrate
@@ -1 +1 @@
-Subproject commit d44f308f9f1e65b158c0d504c65fcb33ffc523ab
+Subproject commit 814b6dd028e67ceb55ac6babac2344f7c1f7c01a
|