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lerobot/notebooks/rlearn_evaluation.ipynb
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2025-08-31 01:02:25 +02:00

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# RLearN Model Evaluation\n",
"\n",
"This notebook provides comprehensive evaluation of the RLearN (Video-Language Conditioned Reward Model) using:\n",
"\n",
"1. **VOC-S (Value-Order Correlation for Success)**: Measures whether per-frame rewards increase as successful execution unfolds\n",
"2. **Success vs Failure Detection**: Tests the model's ability to distinguish correct vs incorrect language conditions\n",
"3. **Live Reward Visualization**: Shows predicted rewards alongside video frames\n",
"\n",
"## Requirements\n",
"\n",
"```bash\n",
"pip install matplotlib seaborn plotly ipywidgets\n",
"```\n"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"/Users/pepijnkooijmans/Documents/GitHub/lerobot\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/pepijnkooijmans/miniconda3/envs/lerobot/lib/python3.10/site-packages/IPython/core/magics/osm.py:417: UserWarning: This is now an optional IPython functionality, setting dhist requires you to install the `pickleshare` library.\n",
" self.shell.db['dhist'] = compress_dhist(dhist)[-100:]\n"
]
}
],
"source": [
"cd /Users/pepijnkooijmans/Documents/GitHub/lerobot"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"✓ Imports successful\n"
]
}
],
"source": [
"import sys\n",
"from pathlib import Path\n",
"\n",
"# Add src to path for imports\n",
"sys.path.append(str(Path.cwd().parent / \"src\"))\n",
"\n",
"import warnings\n",
"\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import torch\n",
"\n",
"warnings.filterwarnings(\"ignore\")\n",
"\n",
"\n",
"# LeRobot imports\n",
"from lerobot.constants import OBS_IMAGES, OBS_LANGUAGE\n",
"from lerobot.datasets.lerobot_dataset import LeRobotDataset\n",
"from lerobot.policies.rlearn.evaluation import (\n",
" RLearnEvaluator,\n",
")\n",
"from lerobot.policies.rlearn.modeling_rlearn import RLearNPolicy\n",
"\n",
"print(\"✓ Imports successful\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 1. Setup Model and Dataset\n",
"\n",
"Load your trained RLearN model and the dataset for evaluation.\n"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Using device: mps\n",
"Loading dataset...\n",
"Dataset loaded: 10 episodes, 1581 frames\n",
"Features: ['action', 'observation.state', 'observation.images.front', 'timestamp', 'frame_index', 'episode_index', 'index', 'task_index']\n",
"FPS: 30\n"
]
}
],
"source": [
"# Configuration\n",
"DATASET_REPO = \"pepijn223/phone_pipeline_pickup1\" # Change to your dataset\n",
"MODEL_PATH = \"pepijn223/rlearn_mse1\" # Change to your model checkpoint\n",
"DEVICE = \"cuda\" if torch.cuda.is_available() else \"mps\"\n",
"NUM_EVAL_EPISODES = 10 # Number of episodes for evaluation\n",
"\n",
"print(f\"Using device: {DEVICE}\")\n",
"\n",
"# Load dataset\n",
"print(\"Loading dataset...\")\n",
"dataset = LeRobotDataset(\n",
" repo_id=DATASET_REPO,\n",
" episodes=list(range(10)), # Load first 10 episodes for evaluation\n",
" download_videos=True,\n",
")\n",
"\n",
"print(f\"Dataset loaded: {dataset.num_episodes} episodes, {dataset.num_frames} frames\")\n",
"print(f\"Features: {list(dataset.features.keys())}\")\n",
"print(f\"FPS: {dataset.fps}\")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"WARNING:root:Device 'cuda' is not available. Switching to 'mps'.\n",
"WARNING:root:Automatic Mixed Precision (amp) is not available on device 'mps'. Deactivating AMP.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Setting up model...\n",
"Loading trained model from Hugging Face Hub: pepijn223/rlearn_mse1\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"WARNING:root:Device 'cuda' is not available. Switching to 'mps'.\n",
"WARNING:root:Automatic Mixed Precision (amp) is not available on device 'mps'. Deactivating AMP.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"✅ Applied torch.compile to encoders and transformer\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "f4455d9dec3d4108b1177dc1a78c3096",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"model.safetensors: 71%|#######1 | 2.20G/3.08G [00:00<?, ?B/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"✓ Model ready on mps\n",
" Parameters: 770,072,581\n",
" Trainable: 19,696,641\n"
]
}
],
"source": [
"# Load or create model\n",
"print(\"Setting up model...\")\n",
"\n",
"print(f\"Loading trained model from Hugging Face Hub: {MODEL_PATH}\")\n",
"model = RLearNPolicy.from_pretrained(MODEL_PATH)\n",
"\n",
"model = model.to(DEVICE)\n",
"model.eval()\n",
"\n",
"print(f\"✓ Model ready on {DEVICE}\")\n",
"print(f\" Parameters: {sum(p.numel() for p in model.parameters()):,}\")\n",
"print(f\" Trainable: {sum(p.numel() for p in model.parameters() if p.requires_grad):,}\")"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"# Create evaluator\n",
"evaluator = RLearnEvaluator(model, device=DEVICE)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 3. Detailed reward visualization"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Visualizing first 4 episodes...\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"objc[5137]: Class AVFFrameReceiver is implemented in both /Users/pepijnkooijmans/miniconda3/envs/lerobot/lib/python3.10/site-packages/av/.dylibs/libavdevice.61.3.100.dylib (0x15327c3a8) and /Users/pepijnkooijmans/miniconda3/envs/lerobot/lib/libavdevice.61.3.100.dylib (0x31943c848). This may cause spurious casting failures and mysterious crashes. One of the duplicates must be removed or renamed.\n",
"objc[5137]: Class AVFAudioReceiver is implemented in both /Users/pepijnkooijmans/miniconda3/envs/lerobot/lib/python3.10/site-packages/av/.dylibs/libavdevice.61.3.100.dylib (0x15327c3f8) and /Users/pepijnkooijmans/miniconda3/envs/lerobot/lib/libavdevice.61.3.100.dylib (0x31943c898). This may cause spurious casting failures and mysterious crashes. One of the duplicates must be removed or renamed.\n",
"W0831 00:56:07.202000 5137 site-packages/torch/_dynamo/variables/builtin.py:861] [0/0] incorrect arg count <bound method BuiltinVariable.call_next of BuiltinVariable(next)> too many positional arguments and no constant handler\n"
]
},
{
"data": {
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",
"text/plain": [
"<Figure size 1600x1200 with 4 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Detailed Episode Statistics:\n",
"================================================================================\n",
"Episode 0:\n",
" Language: Pickup the blue block\n",
" Frames: 128\n",
" VOC-S (Spearman ρ): -0.2463 (p=0.0051)\n",
" Reward range: [0.648, 0.715]\n",
" Trend: ↘ Decreasing\n",
"--------------------------------------------------------------------------------\n",
"Episode 1:\n",
" Language: Pickup the blue block\n",
" Frames: 128\n",
" VOC-S (Spearman ρ): -0.1245 (p=0.1615)\n",
" Reward range: [0.648, 0.715]\n",
" Trend: ↘ Decreasing\n",
"--------------------------------------------------------------------------------\n"
]
}
],
"source": [
"# Static visualization function that works well in VS Code\n",
"def get_episode_data(episode_idx, max_frames=32):\n",
" \"\"\"Extract frames, language, and predict rewards for an episode.\"\"\"\n",
" try:\n",
" # Get episode data\n",
" ep_start = dataset.episode_data_index[\"from\"][episode_idx].item()\n",
" ep_end = dataset.episode_data_index[\"to\"][episode_idx].item()\n",
" episode_length = min(ep_end - ep_start, max_frames)\n",
"\n",
" # Collect frames and get language\n",
" frames = []\n",
" language = None\n",
"\n",
" for frame_idx in range(episode_length):\n",
" global_idx = ep_start + frame_idx\n",
" frame_data = dataset[global_idx]\n",
"\n",
" # Extract image\n",
" if OBS_IMAGES in frame_data:\n",
" img = frame_data[OBS_IMAGES]\n",
" else:\n",
" img_keys = [k for k in frame_data.keys() if \"image\" in k.lower()]\n",
" if img_keys:\n",
" img = frame_data[img_keys[0]]\n",
" else:\n",
" continue\n",
"\n",
" if isinstance(img, np.ndarray):\n",
" img = torch.from_numpy(img)\n",
"\n",
" # Ensure CHW format\n",
" if len(img.shape) == 3 and img.shape[-1] in [1, 3, 4]:\n",
" img = img.permute(2, 0, 1)\n",
"\n",
" # Resize to expected input size (256x256 for SigLIP2) BEFORE stacking\n",
" if img.shape[-2:] != (256, 256):\n",
" import torch.nn.functional as F\n",
"\n",
" img = F.interpolate(\n",
" img.unsqueeze(0), size=(256, 256), mode=\"bilinear\", align_corners=False\n",
" ).squeeze(0)\n",
"\n",
" # Normalize to [0, 1] if needed\n",
" if img.dtype == torch.uint8:\n",
" img = img.float() / 255.0\n",
"\n",
" frames.append(img)\n",
"\n",
" # Get language\n",
" if language is None:\n",
" if OBS_LANGUAGE in frame_data:\n",
" language = frame_data[OBS_LANGUAGE]\n",
" if isinstance(language, list):\n",
" language = language[0]\n",
" elif \"task\" in frame_data:\n",
" language = frame_data[\"task\"]\n",
" else:\n",
" language = \"No language provided\"\n",
"\n",
" if not frames:\n",
" return None, None, None, None\n",
"\n",
" frames_tensor = torch.stack(frames)\n",
"\n",
" # Predict rewards\n",
" rewards = evaluator.predict_episode_rewards(frames_tensor, language)\n",
"\n",
" return frames_tensor, language, rewards, episode_length\n",
"\n",
" except Exception as e:\n",
" print(f\"Error processing episode {episode_idx}: {e}\")\n",
" return None, None, None, None\n",
"\n",
"\n",
"def visualize_multiple_episodes(episode_indices=[0, 1, 2, 3], max_frames=32):\n",
" \"\"\"Visualize multiple episodes in a grid layout.\"\"\"\n",
" n_episodes = len(episode_indices)\n",
"\n",
" # Create figure with subplots\n",
" fig, axes = plt.subplots(2, 2, figsize=(16, 12))\n",
" axes = axes.flatten()\n",
"\n",
" from scipy.stats import spearmanr\n",
"\n",
" for i, episode_idx in enumerate(episode_indices[:4]): # Limit to 4 episodes\n",
" if i >= len(axes):\n",
" break\n",
"\n",
" frames, language, rewards, episode_length = get_episode_data(episode_idx, max_frames)\n",
"\n",
" if rewards is None:\n",
" axes[i].text(\n",
" 0.5,\n",
" 0.5,\n",
" f\"Episode {episode_idx}\\nNo data available\",\n",
" ha=\"center\",\n",
" va=\"center\",\n",
" transform=axes[i].transAxes,\n",
" )\n",
" axes[i].set_title(f\"Episode {episode_idx} - Error\")\n",
" continue\n",
"\n",
" # Plot rewards\n",
" time_steps = range(len(rewards))\n",
" axes[i].plot(\n",
" time_steps, rewards, \"b-\", linewidth=2, marker=\"o\", markersize=4, label=\"Predicted Reward\"\n",
" )\n",
"\n",
" # Add expected progress line\n",
" expected_progress = np.linspace(0, 1, len(rewards))\n",
" axes[i].plot(\n",
" time_steps,\n",
" expected_progress,\n",
" \"orange\",\n",
" linestyle=\"--\",\n",
" linewidth=2,\n",
" label=\"Expected Progress (0→1)\",\n",
" )\n",
"\n",
" # Compute VOC-S\n",
" frame_indices = np.arange(1, len(rewards) + 1)\n",
" correlation, p_value = spearmanr(frame_indices, rewards)\n",
"\n",
" # Format title with key info\n",
" title = f'Episode {episode_idx} (VOC-S: {correlation:.3f})\\n\"{language[:40]}{\"...\" if len(language) > 40 else \"\"}\"'\n",
" axes[i].set_title(title, fontsize=10)\n",
" axes[i].set_xlabel(\"Frame Index\")\n",
" axes[i].set_ylabel(\"Reward\")\n",
" axes[i].legend(fontsize=8)\n",
" axes[i].grid(True, alpha=0.3)\n",
"\n",
" # Add trend indicator\n",
" trend = \"↗ Inc\" if correlation > 0.1 else \"↘ Dec\" if correlation < -0.1 else \"→ Flat\"\n",
" axes[i].text(\n",
" 0.02,\n",
" 0.98,\n",
" trend,\n",
" transform=axes[i].transAxes,\n",
" verticalalignment=\"top\",\n",
" fontsize=10,\n",
" bbox=dict(boxstyle=\"round,pad=0.3\", facecolor=\"lightblue\", alpha=0.7),\n",
" )\n",
"\n",
" plt.tight_layout()\n",
" plt.show()\n",
"\n",
" # Print detailed statistics\n",
" print(\"\\nDetailed Episode Statistics:\")\n",
" print(\"=\" * 80)\n",
"\n",
" for episode_idx in episode_indices:\n",
" frames, language, rewards, episode_length = get_episode_data(episode_idx, max_frames)\n",
"\n",
" if rewards is None:\n",
" print(f\"Episode {episode_idx}: No data available\")\n",
" continue\n",
"\n",
" frame_indices = np.arange(1, len(rewards) + 1)\n",
" correlation, p_value = spearmanr(frame_indices, rewards)\n",
"\n",
" print(f\"Episode {episode_idx}:\")\n",
" print(f\" Language: {language}\")\n",
" print(f\" Frames: {len(rewards)}\")\n",
" print(f\" VOC-S (Spearman ρ): {correlation:.4f} (p={p_value:.4f})\")\n",
" print(f\" Reward range: [{rewards.min():.3f}, {rewards.max():.3f}]\")\n",
" print(\n",
" f\" Trend: {'↗ Increasing' if correlation > 0.1 else '↘ Decreasing' if correlation < -0.1 else '→ Flat'}\"\n",
" )\n",
" print(\"-\" * 80)\n",
"\n",
"\n",
"def show_episode_frames(episode_idx, max_frames=32, show_frames=[0, -1]):\n",
" \"\"\"Show specific frames from an episode alongside reward curve.\"\"\"\n",
" frames, language, rewards, episode_length = get_episode_data(episode_idx, max_frames)\n",
"\n",
" if rewards is None:\n",
" print(f\"No data available for episode {episode_idx}\")\n",
" return\n",
"\n",
" # Create figure\n",
" fig = plt.figure(figsize=(15, 8))\n",
"\n",
" # Reward curve (top half)\n",
" ax1 = plt.subplot(2, len(show_frames) + 1, (1, len(show_frames) + 1))\n",
" time_steps = range(len(rewards))\n",
" ax1.plot(time_steps, rewards, \"b-\", linewidth=2, marker=\"o\", markersize=4, label=\"Predicted Reward\")\n",
" expected_progress = np.linspace(0, 1, len(rewards))\n",
" ax1.plot(time_steps, expected_progress, \"orange\", linestyle=\"--\", linewidth=2, label=\"Expected (0→1)\")\n",
"\n",
" # Highlight selected frames\n",
" for frame_idx in show_frames:\n",
" actual_idx = frame_idx if frame_idx >= 0 else len(rewards) + frame_idx\n",
" if 0 <= actual_idx < len(rewards):\n",
" ax1.axvline(x=actual_idx, color=\"red\", linestyle=\":\", alpha=0.7)\n",
" ax1.plot(actual_idx, rewards[actual_idx], \"ro\", markersize=8)\n",
"\n",
" from scipy.stats import spearmanr\n",
"\n",
" frame_indices = np.arange(1, len(rewards) + 1)\n",
" correlation, _ = spearmanr(frame_indices, rewards)\n",
"\n",
" ax1.set_title(f'Episode {episode_idx} - VOC-S: {correlation:.3f}\\n\"{language}\"', fontsize=12)\n",
" ax1.set_xlabel(\"Frame Index\")\n",
" ax1.set_ylabel(\"Predicted Reward\")\n",
" ax1.legend()\n",
" ax1.grid(True, alpha=0.3)\n",
"\n",
" # Show selected frames (bottom half)\n",
" for i, frame_idx in enumerate(show_frames):\n",
" actual_idx = frame_idx if frame_idx >= 0 else len(frames) + frame_idx\n",
"\n",
" if 0 <= actual_idx < len(frames):\n",
" ax = plt.subplot(2, len(show_frames) + 1, len(show_frames) + 2 + i)\n",
"\n",
" # Convert frame for display\n",
" frame = frames[actual_idx].permute(1, 2, 0).cpu().numpy()\n",
" if frame.max() > 1.0:\n",
" frame = frame / 255.0\n",
" frame = np.clip(frame, 0, 1)\n",
"\n",
" ax.imshow(frame)\n",
" ax.set_title(f\"Frame {actual_idx}\\nReward: {rewards[actual_idx]:.3f}\", fontsize=10)\n",
" ax.axis(\"off\")\n",
"\n",
" plt.tight_layout()\n",
" plt.show()\n",
"\n",
"\n",
"# Visualize multiple episodes at once\n",
"print(\"Visualizing first 4 episodes...\")\n",
"visualize_multiple_episodes([0, 1], max_frames=128)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 4. Success vs Failure Detection Visualization\n",
"\n",
"Test the model's ability to distinguish correct vs incorrect language conditions.\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"==================================================\n",
"DETECTION TEST - EPISODE 0\n",
"==================================================\n"
]
},
{
"data": {
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shMaFWtWKypr5GpZaUSGxAQAAAAAAAL4EiQ03xoGtZX9fRpUHKsWpqwZbawekaoOHHISUA2llsIwH09qLcTuqzhIbtq7wDggMEL3nZYBKBg3BevyalImv7lRryBXNnJRiRduKqPmkoeWUDOweXX1UfSxt6x7wXLYmJC0JDg9Wg8LaKiJ3svervWo1EleVxGXEmf3M47ZExgFz/nySCZvUkamUeX6mmpjVDiPn6xxZcUStfEsalqR+L+tSZc4G2/ftPrv8TD6Z2NDMEemoHZXVFRslhoqN0GgkNgAAAAAAAACsgcSGGzvwywEq2qK0HuFTeyYNulqxEZmmD17rgpB+RMufWG63BEzcQH3QLza941ZUXTH0qqHqeTlsF6zHwTg5PJ57z3eXbEfFwdnCLYW67+VvyFcfK316utu2GgLb2ZKQtLZFkKsSwZbw/ix+eLF6OfPCTJPr6OZs5JRbHByeMjJFBMr7TOojLlccqFATDJwUlAHu/lP7k5+/4X3C1TBcGcJyfsjpsI2StfixJV9rRSVbcVlSf7xePd8jXj+TKiI5QpcckZ9t1gwOF7dPiVA/c5HYAAAAAAAAAF+ExIab4iDYyqdX6rbZM2lgC7kilVf/BoYYgtccSKsp1KyMbicq3FyoW8HbHS0N+h7wMnhjT7JNCzuy3NC+BayjDepVHavq9utTN2fDqB2VtnWOnBsAoCWrhnjmw8njhtXy7oAT03IWggxMd1SlZjxAvHi7YXB46qhUk1ZWsh2VufkaUlBYEA04f4A4X19eT8fWHKPu8smKjV72rdjQJoesbUXFid3ovtHq70b+7EViAwDAtxypPEJ+T/upXyuOrHD1LgEAAAA4lf2mPYNdcbDIeMW6TBoYz55wJF7RW1tUaxLMkUEsbkfFK4S5lRO3ReGAmz2CWxykyf42W7dt9bOrxcBce67UTxqaRD0Seogg35GVR8TPa83gViCTFjgcSObg7YDzlMCpvQeII7EBndG2Q+OqDX5vu01bwceW6bbt+nQXnXHvGbrPM+1nu/EAcf6clVJGpKiJjcUPLVbfixMfmGh2vobW4EsH075vlDZUX1zyBV3x5RXdqpSRQfngiGCzyRpvFN07utuJDU5g+Af6i+q04wcMx9raVlSyHRW/TprrmsXvsKbqJvV71lZ+AAC4Kw7ST/1gqm5bkH8QhQWFUXxYPKXHptOUPlPoryP/Sr2jDX8/dtc/VvyDnl75tDjfN7ovHbn3iMuSFv3/Zfg9vvy65XR2v7Ndsi+erKWthd7d9i59tvsz2l26m6obqykiOEK8hvrH9qcRySPo0sGX0oTeE9TbvL/jfbrhhxs6fO7Pfv9sWnl0Zaevk7XH1tIHOz+gdXnrKL86n+qa6yg6JJoGJw6maf2m0bWnX0sZcabz5UpqS+idre/QksNLKLs8m06cPEFBAUHUL6YfndHzDLp8yOU0c8BM9e/Ifq/2o6NVSsvejrQ/pV+EVnGygl5e/zL9cuAXOlhxkBpbGikmNIbie8RTVkKWeH6M32Mnm0/S65tep2/3fSv2Tf5MfJsBcQPEbf48/M80NMnQGQEAAMBRkNhwUzJpwMkMKXW0fZIGtuChprKvu3ZwOOM/pKbOnUqfzPxEXObkBl+2R+KBEzilu0sdntjhNi39pvYTve+5rz2vik4bowwyhs6Dtdve2WbSiozb3XT1NcCteDgAyAFBTmzwY/B98Urk/I356nWMX4sA5lbSp5yuJABcjT+3tIkJ2V7Q+PNM24pKm9jghGvJzhJxPqZ/jLqqn38f8OyhioMVovqitrhWrcLgORCxGabt+zIvyCS/QD9qb2mnhhMNtPTRpSJR2JX3bGtTK504fEJtQ+Ur7eF0r7O8riU2+HcPV21w1SPPp5JCYqxPSBjP2ZADyMX9oGIDALxQc1szNTc2i+D04crDtPTwUpq7ai49ceYT9MRZT5C/n28tTooLi6N/nvNP9XJGrGmA3Fs0tTZRfXO9CLpbq7m1mWZ+MpOWHdYvLqlsqBRfh04coiW5S8TrSpvYsAdORPz1x7/S99nfm3zv+MnjtObYGvHFyZEV1+srbf69+d/0wKIHqKGlQf/ztDXT3rK94ut/O/5Hh+85LBIdXXW08ihNfm+ySLholdWXiS9OWvD+n55yuprY4OftzPfOpF2lu0x+Jv7af3w//XrgV0oMT0RiAwAAnAKJDTdlnDRg4+8Z7/TAkXYIb2Qv0+HQHMSWCRg+5cv2oFaDbC2i9rZ2EQRyVGJHJjbY4eWHkdiwEgdluf2UuVZkXU0+8eubqzb2/7xfVIDwanA+5kdXHRWJM4ZqDbBEm/BypwHi/BrmZIQcEG3p84xnGHHlQ1Ntk64VFb8Pmuub1cHh2vcLV21seGWDeH8sf2q52sLP0hwargjghA9/tjKuDOxqpRUnNeT70pcC6brKoC5WbDCZ2NCytWJDm9hAKyoA8GZXDb2KxqSNoaqGKtpWvI1+O/gbtba3iq9/rPwHFdcW05sXvkm+JCokih6c+CB5u6dXPE3PrH6GnjzzSZHAstZ/t/9Xl9Tgqguu8gkNDKWimiLaXLhZfNlbXVMdnfvxubSlcIu6LSUihS4edDH1ie5DNU01tK1om0jMGXth7Qv08JKH1csBfgF0wcALaHTqaPIjPzp44qB47ZfUKQtezOFqptvH3N7pfvLjyKRGoH8gXTHkChqSOEQsLMutzBVVJpyo0Pp/a/6fLqnxx0F/pBEpI0Q11bGqY7ShYAP9XvK7Fc8SAACAfSCx4cY4SdAjqQfVlyoDSHllrrNpgzbmVslz4Gz6vOm04O4F4tReiReTapA2+1WDdDhnY9kRmvTQJLs/hjcSQTVeGHdq/rC9WpH1mthLJDbYsbXHxP1p5wZwwBagO7MPnI1X5DfVGVblW/o848tctcFJBw5Uc5KCB0QbDw7XkokNtv3d7er2ftPMr+Djf1a5bZE9Kq208zX4vKyw8nY8q0S2MOzoddZQ0dBpYsOYtTM2ZPWO2cSGH1FweLDV9wMA4Am47c71I65XL+8r20cXfHqBqNxgb219i/6Y9UdxPa2dxTvpXxv/JVbGF9YUikBxZnymCOLeM/4eCg8Ot9j6ilv78OwK6b0/vqfbh59yfqJ3t79Lmwo20fH64+K+RqaMpBtH3iha8Zj7nciB5Nc3vk6LchfRoYpDohIhKTyJRqWOojlj59A5GeeYbSuk3bez+p4lVvlb067qm73fiNX9Wwu3irZDvI+DEwbTZYMvo9vH3k49gvRtO41/3p6RPWnemnm0uWCz+Hkm95lML57zoslq/Ou/v160XLJ3Cy9+rjhxNStzFv39zL/bdNtFhxap5/l54efHWGldqQjI29Mzq57RJTU4+P/pZZ+aPNf8euTXkMSVGI8tfUy9zK+LhVcvpJGpI00qUbhdlvH9Sb2jeluV8NI+P49PeZyeOvspk+vw+4zbv5m7Db8X+DVirhKktklpZQ0AAOBovlWv62H4j8fMWZnqZW4z4mzcp14ynrEhcX/2OXvndKtPuzmyGoTZsxrEGAfOI1KV3vBHVx+l1uZWhzyOtxHDvU8lNezZiszcnA11voYfUb+zu15yDb41Y8NdZP+QTW3NhjdLR59ncoA4Jz+4xZSlweFSn8l91HkKfJuO5muolVZHzVdadSR3SS7NHzJfnJqbscOzmLjyw1fI34dcGcStwrpUsZFsmtiwZTaGrmLjsCGxERIZIqqCAAC8Gc8o+OLyL3TbXtnwiu7ym5vfpDH/GUPv7XiPck/kitY+PA9gR/EO+vuyv9O4d8eJSg9btbW30bXfXUt/+PwP9GPOj+I+uE0Qt+lZfmQ5XfPdNXTV11dRa5v+fwpu0TNk/hB6Yd0LYh945X5jayPlVefRDzk/iDkH9sKPzftw+VeXi8flFf5yH9fnr6cHFz9IY94ZIyoXLOHZFOd9fJ5I+vDzxsHqhQcX0lnvn0VldWXkaKuPrqb7F91PmXGZ9Mmln9jcaozna0j8c3ISwxgnD7gSyF446TB/83xdpQbvu7kkRFpkGt065lZdEocrkKQ3L3jTJKnBeNbGzaNvFvveHdrnJ/t4tpivYe59pm13pb3N4ROHRVs4Y31j+qINFQAAOA0qNtwcB612vr9TnJdDvJ1JuxpVGzR0BkdVg5h7HA4C7vpklxjCykE+bXAdzDu48KDusr2STz3H9lSH6uavyxdzXkp3lapBXXMBQgB3bkW15/M96vnovtEdfp5p52yU55RT0rAkXWLDuGIjICiAMs/PpN2f7zZsCwkQba06nN+0pVAkNRhft6NKK67EWPrYUirfVy5mcgSEBtDuz3bT9v8ZKkQ4kN7dGTueltgo3lEsPqf4MyoyNdJiYoOPR2BYoP0rNiy0okIbKgDwFWN7jqXTk0+nnSXK/0qrjq4SAf0A/wDRRufOBXeKJAQ7o9cZNDNjpkgmcGVBeX25WCHPCYpFf1kk5lPwvApekb44d7G4TWxoLD02xbCCfmzaWLVd0Ee/fyTOc3ugy4ZcJvaDA728nRMIX+39SrTokbfnVexXfHWFmBMhb/eHQX8Q1+EkwbIjhpZJf5/yd1GNwZUS0m2jb1OHTPOK/M7MWz2PvtzzpXqZf/5z08+lfeX7xL4xPn/1t1fTsuv0MyiktXlrxQDpS7MupR0lO0SChPEsBW7z9MjkR8hR+DmZ/c1s0Tbq+9nf2zRbQ+IqmJ/2KxUROcdzqNfLvUQSQ35N7z+dekb1tOt+c2srfo1pW6jJqqDOaFtT8Wvv4qyLu7QPnCh7cd2LJtuHJQ3TVTTx8yMHoH+++3NxfCf0miC2j+85nqb1n0aRIfq/b/h7shUV3zblxRQa32u8aJU1ruc4cZuEHvabhwkAANAZJDbcnKwkYDVFzg/UaYODlio2HElWgzgaz9ngxIacs4HEhm2JDQ6K2iv5FNQjSARvOcFUtreM9n6jzD9h9q4KAu8SFh8mgsitja1u04qq/ni9WsnAn6H35N7T4Wp67XwanrPBSQU5eJxX+JsLoHM7Km1ig39+S3MzzM1v4tkfjVWNFoPqfF/8fmScEHl/yvsm1+Fqke7O2PEk2plT/FrrKLHByVhzn41mExs2zNjg23PCpOVkCxIbAOCzBiUMUhMbXJHB7ZZ4cDEHdmVSg9sQLb12qbrin4PNXK3BOInBMwFOSz5NtO/hqgSZ2DA3w4Lv86X1L6mXeXD501OfVi9zIuBvS/4mzr+8/mUR/OfHfW3ja2pSg3186ceiXZX2fmVLJF6Nb5zYuGrYVSZtpizh+3p146vqZQ5Wr75htUj4sIcXPyyqRhhXmHD1CCdYjHECZdNNm9Tg9qi3R9H2YmVRgyNmU2jd9NNNosri6yu/FnMfuuK+M+4TLZtkWy9OOHG1Cn/J5BK3uHpj1hvdGsKtVVBdoLvMrwerb1tjuO3A+IE2V6hIXJ300OKHTLZfd/p1usTGC+e8QFPemyLaoTGuvvjt0G/ii3FS6ZZRt9BzM55TK06ePvtpUV3ElT/sZMtJUdHDX3JWx+xhs+nV816l+B72n40JAABgDK2oPCix4eqKDXMzNryF8ZwN6Px1Iasoeo7vSXfm3GnXpIM2sbT2+bXqeQwOh45w8Fh+TrlLxUb2d9liVT8betXQTlsEyVZU7HjOcarOq1YD5NrB4VoZ5+krpWT1BCdFOmvzx3gw+fpXlH/yjfF9/HqHskLTBP8ofoYZO3yf3Z2x4ymie0er5/kYmaNNbJhjrhWVLRUb/HqXVRvcioorDhkSGwDgSyz9ruNqA4mDrgH/FyDmR/CXTGpIXN1hrZzyHFHtIf3fqv9T75e/ZFJDVjbI4ctr8tao23nGhTapwTiIba/gOu8jJ3ika067Rk1qsOtGXKe7/vo8838D/OW0v+hW7HOwXTpx8oTuuu9f/D61P9UuvroyX4MD5TwYXrbA4hZfd427iy4dfCl1VXRoNG28aSPdMeYOsxUf7dQu2n+d/8n5Iinma7jCgp8fngHCw7+N8XPy2qbX6I5f7tC1mdp6y1bxmjLXXotbVX38+8eiOsnSexMAAMCekNhwc9pVoK5IbMjgYHBksFcHS2L7x4oWMXKuAw/tBcsO/mao1hgw03RVuD0TG3IeQEBwAPWZ1MfujwXeRVaWcRWCdmC3q2grKYbNHtbp9eMy49RkASc2OhocLumGgRtVT3TU5i9uQJyaaNn46kY6ecIwE0I68OsBOpGrD16w6c9Ppyu/vlJtZ2WvGTveMqief4dwwqjDxEZS92ZsMJnY0P7OsvU+AAA8mUwcyBXmcpW4NrDfGVvmRdhyv9r71t6uf6xjF+oY72NyeHKHl080mP6eZ8aJlpBAw+8XWQ1jD1wxw22ibv35VjFc/YFFD4gqjefPeb7b950ckUzzL5hP5Q+V05abt9C/Z/2brhx6JYUEGH6W7PJstc0WMw7ym0t6cKWCFBwQrJ43bm3F920tHtSufV13NTHAw+Vlkkn7xcknY1ypw62+Kh+pFMPVn5v+nEllELdu076m0mPT6aNLPqITD5+gdX9dR6+c9wpdkHmBrsKEK4FkdQ8AAIAjoRWVm+uR0EOdN+DsVlT8x5QM2HhztYa2amPHeztEgCh/Qz6GVHfg0ELDkOAB5zs2saHdxm2qADqinQXEiVlXVhDUFtfSkeXKqsXYjFhKHW2+4kIrKCyIYvrGiNZC3Iqqo8HhEv+MiUMTRes2TjRw9QRft6OfnSus7jpwF/10y0+07T/bRBuj9S+vp2lzp6nXaaptokUPLtLdTt73pIcmictiXsfmQrvN2PGWxIY2SdQj3nRFoz1mbBjP2ZC8eRECAIDWlsItahsqGdCVwdW4sDh1WPTkPpPFqnRLJvaeaPVj8v0at/fh2QWWyOSA9nY8i8ORjPeRB4d3dJnnOZjDQ6q1uHWTI3AigYeTf7vvWzpQcUAkEnjgNieq7IUrVkanjRZft4+9XQwmP/P9M9XvHzh+QD3Prcy0jI8X/4/MrcLMXZ/nsEQGR6pzNnjOybzp88xWNxjjmR/888tkE7d86uqcDVvx/nFCg7+4fdrclXPpyRVP6p4fnqWhxQmdCb0niK97z7iXPtr5EV37/bW62/BMDgAAAEdCxYab49W0YUnKas+aQucmNrjnulxx6or5Gs7GczYknrMB5nGS7dDiQ+pK5LQxhpY29sKvt+g+hlYvDG2owNbERnWBa+ds7P16r6iekNUa1lYzyAHinGw4uOBgpxUbfL/nvnRul6onpvx9CvkHKX8KbPzXRrV9Ev/T/vOtP9PxbH3Vh/a+ZeVHwuAEu83Y8RRRvQ2/E7e+vZVyl+Tqvn/yuCGxERpnPjATkWxoNdmVGRsMiQ0A8FXcbmn217N12+6fcL/ZZEVxbTHdMvoWMS9D+zVn7BxKCk/SXVe7Wl87E0M70yM+LF63ct/4fvnr2tOvFQPJe0cri3Um956s3oaHdvOwZi3+vStnbBjvh6V9sYT3UZvc4NZAPFRd+mDHB11O7Fhy/ffXq+24+r1q2+KwwYmDRXsunoGxrWgbzZ061+zMD1vxjJNPd31qtuIiIlj/O1jbqooHiwf4GVp3vbnlTV3Fwttb31aTZowHbWuTQXeMNbRuKqotor989xc62WxaFVtYU0jvbH1HvXznuDt1j3v7L7fTzmJD4k5qbm0W7bq0+9AVd/16l2jTZq4yxNLz8/iyx+nn/T+LllPW3gYAAMCRULHhAXok9aC6wjqqK60TQWWu4HAG7SpUbbDQW/WfajRnwzAHEDS4moWTXoxXaPsHOOb12GtCL6o6prShYv2moYIGur+S3lVtqHi+hrV4zsah35TkYcGmAjVYzS3zLJFzM2ytnuDqkJF/HSmC8001TbTupXU0/dnp4vKuT3eJ6wRFBInH5rk6xvfNlR9z9s4hX6OtYuQE1NLHlorkq0zuyARRR62oeiTqV29ygomHgdsipj8SGwDgGxYeXChmW/CAY25xw5e1wVVOUpybca56+YEJD9AP2T+IOQoHKw7SsH8PE/MauA1TVWMV7SrdRSuPrBSVApyEMNdKqKy+jG744QYakjBEfL7zY4QFhYkEyt+X/V1dkc/Dms9JP0es1OckypaiLbQxf6OoFLlk8CXienePv1sEyGULoz9/82f6Ys8XNCJ5hFidzwFmXi3/6sxX1SoATm5wsJ/x43GQmwPnfD0OvlvCVSs8OPuJ5U+Iyzwse/J7k+nc9HMp+3i22Gdpar+pdHrK6eRqvOKfZznwcGvjge3daXHFba34uJzZ90wanjRcDITnZAM/9xInE87JOEe9zEkhHtbOSRHGr5X0f6WLyhyem6JtL8XDsjlppvX4mY+LAfScpGFciZKRl0GXZF1CvaJ6iWoO/t7Sw0tpUu9J6u2HJg0VSZ3Hlj0mLvNracx/xtCFAy+kkSkjRcXMwRMH6beDv4mqmxnpM8z+3HnVefTiuhfNfu+qoVepybaf9v9Eb2x+g9Ii00S1U2ZcpqjCyDmeo3t++sf0V+errDm2hp5d/axI7p3V7yyRkAoPCqfDlYd1yTp+nu2RMAMAAOgMEhseoEfyqeBHO4nkRmSac5IM2tXOvlCxwT8j97evOFBBx9Yco5yfc2jQhYNcvVtu5+BCwwryjJmOaz1jvMq5sVJJpgBYG3B25QDxqrwqylubJ84nDkmkpGFJVt9WVmxopYxI6XDwuKyeWHD3ApurJ6Y8NoW2/287tTW30YaXN9DvH/2um+l08XsXixZJXblvb8Vt8YIjgkW7LsYJpUOLDtGA8wZYndgIDAkU8zBkopirNWx9blGxAQC+ggOt2mCrNrD81FlP0WNTlGCwxEmFN2a9QfcsvEckQDjY+6+N/+r0cTiwzm15ZIXE+zsMcwmuH3G9SGxwqx4Obn/0+0dqSyz+6ggPXf76yq9FlQkHtjnh8n329+JL0s424AAzB7S/y/5OXN5RvEN8sX+e888OExvs0cmPisD+V3u/Epc35G8QX1oclP740o/JHXBw3zhBYC/8fPOQcP4y5/+m/p+YG6H1xvlv0L6yfeqcCE6GaQfSy9femxe8SVkJWSaVC4uuWUTX/3C9qG5gnEz595Z/d7qvj055lMKDw+lvi/9Gja2N4rVr/DrpDCfaHlr8kNnv8etGJja0lSOf7f7M7PW5Hdi7f3jX5O8TTvBwwsZSYm3+rPm6wfMAAACOgsSGh1RsSDxnw2mJDR+r2JDtqDixwRY/sJgGXjAQQTwj2tY4Mohnb6Icf6WhHJ+t+McKMc8DxwOsrthwYSuqPV/uUc8PnT3UptdtwqAEk22W2lBpdbV6gtu+jbxxJG19a6uYMVSdZ3jext8znoZcPkSc98XKjI4+o9pa23SzR5Y/sVxUs/CxtiaxIedsyMRGV4Z+I7EBAL6EV9Zz0iGhR4IIRPMq/BtH3mgysFnilkB8ndc3vk4rjq4Qg6mbWpvEanMORvP3Lh9yue42KREp9NOffqInlz8pEglc0WEucPvhJR/S7GGz6X/b/0cbCzaKtkC8op5vf1ryaWJeAg+p1pqVOYv23LGHXt/0Ov126DcRgG5saRTVGbwin7+v9Z+L/iNWvnN1CleP2DKwm2dKfHnFl/T13q/pvR3vicQLt1Pi1fX8s/PPffuY20UQ3Vs9P+N5UUmz7PAyMYuFqxzkMPfUyFTRQurW0bfS1P5TTW4bGxZL629cT//d/l/xHHLVRmVDpUg49Y7qLV473DqKj7U5PMSeX0erjq6iD3d+SOvy1lFBTQHVNdVRdGi0GI7+h4F/EJUhxri654ohV4g2VUsOLxFt17iqhx+7b3RfkQDjygs+3x2/XfMbLcldQsuOLBPDyvk1zK8RHqzOiTiu5uFKmgFxhv/3+HW/+NBicZs9pXvEbbiSipM8XI0yqc8kumvcXZitAQAATuPXbq6pIqiqq6spOjqaqqqqKCrK+VULbW1t9OvDv9LWF7eKy3/66U808EKlFNTRVv7fSlrx1ApxfvaPs2nQRd5fvbDksSW09jnDapyrF15t9+A9H9PS0lJKSko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"text/plain": [
"<Figure size 1600x1000 with 4 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Episode 0 Detection Analysis:\n",
" Correct language: 'place the white sponge in the ceramic bowl'\n",
" Incorrect language: 'kick the ball'\n",
" Final reward (correct): 0.2294\n",
" Final reward (incorrect): 0.0995\n",
" Difference: 0.1300\n",
" Detection: SUCCESS\n",
"\n",
"==================================================\n",
"DETECTION TEST - EPISODE 1\n",
"==================================================\n"
]
},
{
"data": {
"image/png": 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"text/plain": [
"<Figure size 1600x1000 with 4 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Episode 1 Detection Analysis:\n",
" Correct language: 'move the arm in a circular motion'\n",
" Incorrect language: 'dance in place'\n",
" Final reward (correct): 0.6490\n",
" Final reward (incorrect): 0.9115\n",
" Difference: -0.2625\n",
" Detection: FAILURE\n",
"\n",
"==================================================\n",
"DETECTION TEST - EPISODE 2\n",
"==================================================\n"
]
},
{
"data": {
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"text/plain": [
"<Figure size 1600x1000 with 4 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Episode 2 Detection Analysis:\n",
" Correct language: 'place the bottle in the ceramic bowl'\n",
" Incorrect language: 'wave your hand'\n",
" Final reward (correct): 0.6576\n",
" Final reward (incorrect): 0.0815\n",
" Difference: 0.5761\n",
" Detection: SUCCESS\n",
"\n",
"==================================================\n",
"DETECTION TEST - EPISODE 3\n",
"==================================================\n"
]
},
{
"data": {
"image/png": 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bLjAw0FxZp8+jy1kbROp6Oa+7dZ3sfzrTaqGXXnpJateubX7X59RgQkM4fS3r4wYPHmyqWSIiImTIkCEmrPvjjz/Me/n111/l2WefldGjR5vvq36/rGGZ8+va33Zetxuti3739Pn139PcuXPlzz//NMtbn0MnDYPuvfdeEyTqv9XLly+bf5caQjlfpZhe1tdw9d1H5rD+jeHz909s/xvQMLlhQ8vkTKs9dEirf6YA+9/dBb9//WWZVq9OcVdyiRKW4awqVZLkf35ab0u+fB54c2x/f+ft7Z8Vv3e6D3r69Gmzz6XBg+7X6z6ttUG4XpCj+09WWtWt+0+6H6cXSuk+nV4gohfOWOlFVdZjHPXYY4+Zn7pPdrMX0QAAAADIAsGGVjps2bLF4eonPWBo1apViivYrXS+fUM9pRUeeiBhf6ChBxJPPfWUlCxZ0pw4379/vzl5nZF0XXQoLOsBj3Vd9Aqv3377TerVq5fiMXoy3hqY2NMDqStXrqQYYkkP/PSkv7XyQEON4xeO3/K6X0+6nu7nScsQW3olmh4o68FdasvryXodokq3i7Uh4scff2wOIrWqQ6sH9L3rd0TnF9WGsXbroAeGWjlgpdtaw67H9apbESlbtqw5aNQDTQ0RNPzSYGvnzp2mgsS6jFX+/PlNpYKOsZza+7UeiLt7bxrW2NNATb+D+rp6oGt9nAYI+l1RekCs71tDFR1i7f333zdhgzV802BOww4dcs36eGsYYL8e1qDAOu9G66IVTfqeNRTUyhf9XPTfloYq1u+crouu25tvvunwPFoRo8GQ9bO8Gfr8+h7Onj0ruXLluunnwc3Tz18rlfR7Y3+yBv6B7X+LypWzTE59owJiYyXH4cOS88gRyXHokOXn4cOWSatAXAg4cUJEpzVrJMDpvsTwcEmsUEGuV6jg8DOxfHlJvoXQg+3v37y9/fVCk6xIL7Kxr7iw5+piKK3s1skdrbDVCQAAAEA2CzZ0OBsdzsk+GFB623rlvDO9gsrV8vYl3ZMmTTIng7XHhl4BrwdsWlp+9913Z+j6u1sX632uaIhjH8zoVfN6Yl9P3OtwTPY06NADP30POlkrJ9JDKzY0xHCWMzBnuis2rOuQGuvBsVZXpLa8NdDQIaastLJAh03S+26//XbzXOXKlZMSeiWrk0aNGjk8v56s10odrXKw0u+WfoYajmiIot8H7beS2nrf6D3eaDmtutBAZcOGDeb7bQ1C/vrrLxMQWB9n/7s12NFqF52nz6HDTNm/hvae0WDDOk/XQyf7ZazDaFnn3Whd9H79zDXUsAYL+rlb359OOgyVHsgXKlQoxXvVCg93n2daWP9t6jBZ1mHGkLn0O6HfGf37w4lN/8P295DwcEu1hQtJsbHuKz3cDMGZIybGTLl1WCwnybrP4arSQxua58+f6mqy/f2bt7c//+8DAAAA8PmhqDxBgw296l+rNvTEuA5TpE2r9Wp1rQbxpqCgIDM5s56odp5nPVmtk9r8zOab6rERIAFmGCrrzy8e+UIerv6w7Qp/PclsfY1boVfw6/No5UZqz2e9z9Uy9u9ZT7q7WkaHirKfr0MtaSVMR23i6kT7R+iwWO5e70brk57ldGgn/c5pkKbfNz1xoNURWn1jvx11mDLr79btrtvC/vntX8P5da3DWtkvY63UsM5L67q4ek3r7/q5tm/fXt7R8eCdaOB0K98Z62u4+u4j87AN/BvbP5NpSNyokWVypqGH9kHSoOOPPxx/2vWfsheg83X65ZcUlR62gEVDDuef/1xIwfb3b97c/nznAAAAAPh0sKHD/uiV/fYNo5XeLl7cdWWCzk9tee0BoMMPff3116axt9Kr0rVR33vvvZehwYa+pg5v5Lwu1vuygo7VO8pXj34lb65+U/ad3SdVi1SVYc2HmVDDEwoXLmyGWJoyZYq8+OKLJpiwpz0btCqjevXqcvToUTNZKxZ0aCO9/2aqALRpuIYplfWEjQv6HTh27JipBnE1fJIGDVrhcSt0SCVdBw0StM+H+uWXX9L9PFWrVpVNmxz7mTjf1isstZrCnn7HrZUXaVkXfR0djkp7vlirPJxfRz9X7W9Svnz5NFXsAABuUmio/tG1TM60H5e70MNdE2KtANHp119T3le0qAREREioNjSvVcsSeFhDD10PAAAAAACyOK+eqdSTyQ0aNDBNiHXoHaVXlettd+PbaqNnvd/af0Bp/wSdr/RqdJ2crwTTACWjGxXqa44cOVJiYmIkXK+M/GdddEipWxmixxPhhk6ZRUONO+64Qxo3bmx6M2iooNUE+tn897//lT179piASfuTaE+MCRMmmPuff/55ad68uemvkV7a6PHBBx80fTMeeeQRs/137NhhTv5rI3N9Xh2KrFOnTqYJtgYgOtyZXq2o/Sz0xL1WJ+h3q06dOqbCw1rl4UwDEA0R7GkVjgYFOqzStGnTTDWDNpnURtvp9cILL5h11fXUaomffvpJvv/+e4fqCG3orc3H58yZY76HGlDoe7X2ddGho260Lv/6179M/xHtCaNDpGnIpOGfsr6WVjppOKLNzV999VUTXGlD93nz5slHH31k/l0BADxMKyz077uL3l2ivQrchR7at8OV06cl4PRpCdHfFyxwvE97Tbmr9NCG6gAAAAAAZAFevwRb+010797dnMzWE+F6kjs+Pl6ioqLM/d26dZNSpUqZptuqT58+5iT12LFjTUWGnmDdvHmzOYGrNFTQ+7WRtA5BpEPxrF692pwA1hPFVtoDQyc9Sau0B4M2kNYT43ryVunJYO17oD/tT2brSXEdCun+++83AYY2sX733XfN82kjaD0Z7Gq4KX+hjaW3bt1qQp+XX35ZTpw4YSoMNMTSYMN64vx///uf7SS+BhEaMOgwYjdDq0S+/fZbE6TosElauaCNuJ9++mnbMlp58Morr5iT9Pod0+1o7cmhDee1aXaXLl1MtYP2pnjjjTdcvpYGIM6N4StVqmQ74a+VKjrkkwYd2ny7RYsW6XovGgpNnTrVDK2l3yd9b9psXJt827/f119/3YQN2kdEm6frvxX9Hiv9PG+0LvpvRYdr02BD348GTRoQaeBhHftah7DSxuWvvfaa+b5rdYf+m9JtxTASAJAFaC+NunUtk7OLF92HHn/95fr5zpyxTOvWpbyvSBH3oYeLXkwAAAAAAHhKQLIO1O9lesJWrz7XYECbGusJWG2WrPRErF5NP2vWLNvyCxYsMCd8jxw5IhERESZUaNu2re1+fR69An3ZsmUmmNATsdpMXE8OW69E15PWeuLY2cyZM+XJJ580v+vP2bNnp1hm5cqVthPE2kBZTwxrg2UddklDGj1ZntZhe7R5eGhoqMTGxrpsHn748GHTYNtTTRYzuscGPKNnz56mwuTnn3/26Pb/7LPPTKio30cNBj0pM77fSJ1WsVkrzgiq/A/b378lXbgg5zZtksLnzkmgc/hx/Hj6n1AvCnEXevxzwQiyDm//+09t/xdZ77Nq/3l7r7wuAP+zuOtib69C1tWev8UAMtHixT6x/5slgg1/RrABV3RIqPvuu8+EZToMlVa+fPDBBw4VKBlBgzsN/rRSaefOnWYIOA3tdGgrTyPY8D5vn9iCd7H9/Vuq2z8+XuTQof8POuxDj2PH0v9iWs3hLvTQKhD43b//rHCy3ldkhc+KYANAZiHYSAXBBoDMtNg3gg2vD0UFICVtSq+VSBcuXDBDe2kVU0aHGtbqJh12S39qL47OnTubIcQAAH4sb15LU3GdnF265D70OHrU9fP9/bf+x2aZXIUe9kGHc+jBRRcAAAAAABcINoAs6IsvvsiU19EeHdrnhoodAECa5MkjUrOmZXJ2+XLqoYerImENPTZtskzOtFm5u9BDm5zz/xYAAAAA+C2CDQAAANw67c10222WydmVK+5Dj+ho16HH+fMimzdbJmehoe5Dj6JFCT0AAAAAIJsj2AAAAIBnaS+lGjUsk6vQ4/Bh16HHn3+6Dj1iY0W2bLFMznQcVnehR3g4oQcAAAAAZAMEGwAAAPBu6FG9umVydvVq6qFHUlLKx8TFiWzdapmc5c/vPvQoVozQAwAAAAB8BMEGAAAAsqagIJFq1SyTq9DjyBHXoYfOdxV6XLggsm2bZXKWL5/70KN4cUIPAAAAAMhCCDYAAADgm6FH1aqWydm1a6mHHomJKR9z8aLI9u2WyVnevO5DjxIlCD0AAAAAIJMRbAAAACB7yZ1bpEoVy+Qq9NBhrFyFHjrslavQIz5eZMcOy+QsTx73oUfJkoQeAAAAAOABBBsAAADwr9BDgwednCUkpB56XL+e8jGXLons3GmZnIWEpB56BAZ65j0CAAAAQDZHsJHdRUeLnDmTcn5YmEjZsh55ySeffFLOnz8vixYtkuyoRYsWUrduXZkwYUKGLAcAALKIXLn+P4BwFXrofpWr0OPQIdehx+XLIrt2WSZXoUelSq5Dj1KlCD0AAAAAIBUEG9mZHnzruNNXrqS8LzhYZN8+kTJlJDu6du2a5NYrMu0kJiZKQECABHKiAAAA3EzooUGETs401Egt9NBQxFXosXu3ZXK1n+Yu9ChdmtADAAAAgN/jqCg700oNV6GG0vmuKjk8QCsXXnzxRXn11VelcOHCUrx4cXnjjTccltEKj//85z9SrFgxCQ4Olpo1a8q3335ru/+rr76S2267TYKCgqR8+fIyduxYh8frvBEjRki3bt2kQIEC8swzz8isWbOkYMGC8s0330iNGjXMY6Ojo+Xq1avyyiuvSKlSpSRv3rzSpEkTWbVqlcPz/frrr2a98+TJI4UKFZLWrVvL33//bapRVq9eLRMnTjQhiU5HtAnpTXjttdekSpUq5jUqVqwor7/+uiTYnfjQz0grPj755BPz/kJDQ+Wxxx6TCxcu2JbR3x9//HHzPkqUKCHjx4836923b1/bMrqOztUz+rno55PWdVFvvfWWhIeHS/78+eXpp5+WAQMGmPWz99FHH0n16tXNNqxWrZp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"text/plain": [
"<Figure size 1600x1000 with 4 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Episode 3 Detection Analysis:\n",
" Correct language: 'drag the ceramic bowl in a circle'\n",
" Incorrect language: 'jump up and down'\n",
" Final reward (correct): 0.0812\n",
" Final reward (incorrect): 0.0811\n",
" Difference: 0.0001\n",
" Detection: SUCCESS\n"
]
}
],
"source": [
"# Test success vs failure detection with visualization\n",
"def compare_correct_vs_incorrect_language(episode_idx, max_frames=128):\n",
" \"\"\"Compare rewards for correct vs incorrect language for the same episode.\"\"\"\n",
"\n",
" # Get original episode data\n",
" frames, correct_language, correct_rewards, episode_length = get_episode_data(episode_idx, max_frames)\n",
"\n",
" if correct_rewards is None:\n",
" print(f\"No data available for episode {episode_idx}\")\n",
" return\n",
"\n",
" # Generate incorrect language\n",
" incorrect_languages = [\n",
" \"kick the ball\",\n",
" \"clean the sink\",\n",
" \"go to the threepickup the twixdo nothing\",\n",
" ]\n",
" incorrect_language = incorrect_languages[episode_idx % len(incorrect_languages)]\n",
"\n",
" # Predict rewards with incorrect language\n",
" incorrect_rewards = evaluator.predict_episode_rewards(frames, incorrect_language)\n",
"\n",
" # Create comparison plot\n",
" fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(16, 10))\n",
"\n",
" time_steps = range(len(correct_rewards))\n",
"\n",
" # 1. Reward curves comparison\n",
" ax1.plot(\n",
" time_steps, correct_rewards, \"g-\", linewidth=2, marker=\"o\", markersize=4, label=\"Correct Language\"\n",
" )\n",
" ax1.plot(\n",
" time_steps, incorrect_rewards, \"r-\", linewidth=2, marker=\"s\", markersize=4, label=\"Incorrect Language\"\n",
" )\n",
" ax1.set_title(f\"Episode {episode_idx} - Reward Comparison\")\n",
" ax1.set_xlabel(\"Frame Index\")\n",
" ax1.set_ylabel(\"Predicted Reward\")\n",
" ax1.legend()\n",
" ax1.grid(True, alpha=0.3)\n",
"\n",
" # 2. Final reward comparison\n",
" final_correct = correct_rewards[-1]\n",
" final_incorrect = incorrect_rewards[-1]\n",
"\n",
" ax2.bar(\n",
" [\"Correct\\nLanguage\", \"Incorrect\\nLanguage\"],\n",
" [final_correct, final_incorrect],\n",
" color=[\"green\", \"red\"],\n",
" alpha=0.7,\n",
" )\n",
" ax2.set_title(\"Final Reward Comparison\")\n",
" ax2.set_ylabel(\"Final Reward\")\n",
"\n",
" # Add values on bars\n",
" ax2.text(0, final_correct + 0.01, f\"{final_correct:.3f}\", ha=\"center\", va=\"bottom\", fontweight=\"bold\")\n",
" ax2.text(1, final_incorrect + 0.01, f\"{final_incorrect:.3f}\", ha=\"center\", va=\"bottom\", fontweight=\"bold\")\n",
"\n",
" # 3. Reward difference over time\n",
" reward_diff = correct_rewards - incorrect_rewards\n",
" ax3.plot(time_steps, reward_diff, \"purple\", linewidth=2, marker=\"d\", markersize=4)\n",
" ax3.axhline(y=0, color=\"black\", linestyle=\"--\", alpha=0.5)\n",
" ax3.set_title(\"Reward Difference (Correct - Incorrect)\")\n",
" ax3.set_xlabel(\"Frame Index\")\n",
" ax3.set_ylabel(\"Reward Difference\")\n",
" ax3.grid(True, alpha=0.3)\n",
"\n",
" # 4. Language descriptions\n",
" ax4.axis(\"off\")\n",
" ax4.text(0.1, 0.8, \"Language Conditions:\", fontsize=14, fontweight=\"bold\")\n",
" ax4.text(0.1, 0.6, f'Correct: \"{correct_language}\"', fontsize=12, color=\"green\")\n",
" ax4.text(0.1, 0.4, f'Incorrect: \"{incorrect_language}\"', fontsize=12, color=\"red\")\n",
"\n",
" detection_success = \"✓ SUCCESS\" if final_correct > final_incorrect else \"✗ FAILURE\"\n",
" color = \"green\" if final_correct > final_incorrect else \"red\"\n",
" ax4.text(0.1, 0.2, f\"Detection: {detection_success}\", fontsize=14, fontweight=\"bold\", color=color)\n",
"\n",
" plt.tight_layout()\n",
" plt.show()\n",
"\n",
" # Print statistics\n",
" print(f\"Episode {episode_idx} Detection Analysis:\")\n",
" print(f\" Correct language: '{correct_language}'\")\n",
" print(f\" Incorrect language: '{incorrect_language}'\")\n",
" print(f\" Final reward (correct): {final_correct:.4f}\")\n",
" print(f\" Final reward (incorrect): {final_incorrect:.4f}\")\n",
" print(f\" Difference: {final_correct - final_incorrect:.4f}\")\n",
" print(f\" Detection: {'SUCCESS' if final_correct > final_incorrect else 'FAILURE'}\")\n",
"\n",
"\n",
"# Test detection on multiple episodes\n",
"detection_episodes = [0, 1, 2, 3] # Change as needed\n",
"\n",
"for episode_idx in detection_episodes:\n",
" print(f\"\\n{'=' * 50}\")\n",
" print(f\"DETECTION TEST - EPISODE {episode_idx}\")\n",
" print(\"=\" * 50)\n",
" compare_correct_vs_incorrect_language(episode_idx)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "lerobot",
"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": "3.10.13"
}
},
"nbformat": 4,
"nbformat_minor": 2
}