Add keyframe saving to video content sample (#26)

* Add implementation of saving keyframes in the Video Content sample

* Remove notebook outputs

* Update notebooks/content_extraction.ipynb

Co-authored-by: Copilot <[email protected]>

---------

Co-authored-by: Copilot <[email protected]>

Author: hustcalm

notebooks/content_extraction.ipynb

@@ -75,7 +75,21 @@
     "    api_version=AZURE_AI_API_VERSION,\n",
     "    token_provider=token_provider,\n",
     "    x_ms_useragent=\"azure-ai-content-understanding-python/content_extraction\", # This header is used for sample usage telemetry, please comment out this line if you want to opt out.\n",
-    ")"
+    ")\n",
+    "\n",
+    "# Utility function to save images\n",
+    "from PIL import Image\n",
+    "from io import BytesIO\n",
+    "import re\n",
+    "\n",
+    "def save_image(image_id: str, response):\n",
+    "    raw_image = client.get_image_from_analyze_operation(analyze_response=response,\n",
+    "        image_id=image_id\n",
+    "    )\n",
+    "    image = Image.open(BytesIO(raw_image))\n",
+    "    # image.show()\n",
+    "    Path(\".cache\").mkdir(exist_ok=True)\n",
+    "    image.save(f\".cache/{image_id}.jpg\", \"JPEG\")\n"
    ]
   },
   {
@@ -184,6 +198,27 @@
     "result = client.poll_result(response)\n",
     "\n",
     "print(json.dumps(result, indent=2))\n",
+    "\n",
+    "# Save keyframes (optional)\n",
+    "keyframe_ids = set()\n",
+    "result_data = result.get(\"result\", {})\n",
+    "contents = result_data.get(\"contents\", [])\n",
+    "\n",
+    "# Iterate over contents to find keyframes if available\n",
+    "for content in contents:\n",
+    "    # Extract keyframe IDs from \"markdown\" if it exists and is a string\n",
+    "    markdown_content = content.get(\"markdown\", \"\")\n",
+    "    if isinstance(markdown_content, str):\n",
+    "        keyframe_ids.update(re.findall(r\"(keyFrame\\.\\d+)\\.jpg\", markdown_content))\n",
+    "\n",
+    "# Output the results\n",
+    "print(\"Unique Keyframe IDs:\", keyframe_ids)\n",
+    "\n",
+    "# Save all keyframe images\n",
+    "for keyframe_id in keyframe_ids:\n",
+    "    save_image(keyframe_id, response)\n",
+    "\n",
+    "# Delete analyzer\n",
     "client.delete_analyzer(ANALYZER_ID)"
    ]
   },
@@ -229,21 +264,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from PIL import Image\n",
-    "from io import BytesIO\n",
-    "import re\n",
-    "\n",
-    "\n",
-    "def save_image(image_id: str):\n",
-    "    raw_image = client.get_image_from_analyze_operation(analyze_response=response,\n",
-    "        image_id=image_id\n",
-    "    )\n",
-    "    image = Image.open(BytesIO(raw_image))\n",
-    "    # image.show()\n",
-    "    Path(\".cache\").mkdir(exist_ok=True)\n",
-    "    image.save(f\".cache/{image_id}.jpg\", \"JPEG\")\n",
-    "\n",
-    "\n",
     "# Initialize sets for unique face IDs and keyframe IDs\n",
     "face_ids = set()\n",
     "keyframe_ids = set()\n",
@@ -273,11 +293,11 @@
     "\n",
     "# Save all face images\n",
     "for face_id in face_ids:\n",
-    "    save_image(face_id)\n",
+    "    save_image(face_id, response)\n",
     "\n",
     "# Save all keyframe images\n",
     "for keyframe_id in keyframe_ids:\n",
-    "    save_image(keyframe_id)"
+    "    save_image(keyframe_id, response)"
    ]
   },
   {