Update download_api.py

download_api.py

@@ -5,6 +5,7 @@ import threading
 from fastapi import FastAPI, HTTPException, BackgroundTasks
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import JSONResponse, FileResponse
+from fastapi.staticfiles import StaticFiles
 import uvicorn
 from typing import Dict
 from pathlib import Path
@@ -13,18 +14,18 @@ from datetime import datetime
 
 import torch
 
-
 # Import from vision_analyzer (previously cursor_tracker)
 from vision_analyzer import (
     main_processing_loop,
     processing_status,
     ANALYSIS_OUTPUT_FOLDER,  # Changed from CURSOR_TRACKING_OUTPUT_FOLDER
-    log_message
+    log_message,
+    FRAMES_OUTPUT_FOLDER  # Add this import for frames directory
 )
 
 # FastAPI App Definition
 app = FastAPI(title="Video Analysis API", 
-             description="API to access video frame analysis results", 
+             description="API to access video frame analysis results and extracted images", 
              version="1.0.0")
 
 # Add CORS middleware to allow cross-origin requests
@@ -71,6 +72,9 @@ async def root():
             "/status": "Get processing status",
             "/analysis-data": "List available analysis files",
             "/analysis-data/{filename}": "Get specific analysis data",
+            "/courses": "List all available course folders",
+            "/images/{course_folder}": "List images in a course folder",
+            "/images/{course_folder}/{frame_filename}": "Get specific frame image",
             "/start-processing": "Start processing pipeline",
             "/stop-processing": "Stop processing pipeline"
         }
@@ -82,9 +86,97 @@ async def get_status():
     return {
         "processing_status": processing_status,
         "analysis_folder": ANALYSIS_OUTPUT_FOLDER,
-        "folder_exists": os.path.exists(ANALYSIS_OUTPUT_FOLDER)
+        "frames_folder": FRAMES_OUTPUT_FOLDER,
+        "analysis_folder_exists": os.path.exists(ANALYSIS_OUTPUT_FOLDER),
+        "frames_folder_exists": os.path.exists(FRAMES_OUTPUT_FOLDER)
     }
 
+# ===== NEW IMAGE SERVING ENDPOINTS =====
+
+@app.get("/images/{course_folder}/{frame_filename}")
+async def get_frame_image(course_folder: str, frame_filename: str):
+    """
+    Serve extracted frame images from course folders
+    
+    Args:
+        course_folder: The course folder name (e.g., "course1_video1_mp4_frames")
+        frame_filename: The frame file name (e.g., "0001.png")
+    """
+    # Construct the full path to the image
+    image_path = os.path.join(FRAMES_OUTPUT_FOLDER, course_folder, frame_filename)
+    
+    # Check if file exists
+    if not os.path.exists(image_path):
+        raise HTTPException(status_code=404, detail=f"Image not found: {course_folder}/{frame_filename}")
+    
+    # Verify it's an image file
+    if not frame_filename.lower().endswith(('.png', '.jpg', '.jpeg')):
+        raise HTTPException(status_code=400, detail="File must be an image (PNG, JPG, JPEG)")
+    
+    # Return the image file
+    return FileResponse(image_path)
+
+@app.get("/images/{course_folder}")
+async def list_course_images(course_folder: str):
+    """
+    List all available images in a specific course folder
+    
+    Args:
+        course_folder: The course folder name
+    """
+    folder_path = os.path.join(FRAMES_OUTPUT_FOLDER, course_folder)
+    
+    if not os.path.exists(folder_path):
+        raise HTTPException(status_code=404, detail=f"Course folder not found: {course_folder}")
+    
+    # Get all image files
+    image_files = []
+    for file in os.listdir(folder_path):
+        if file.lower().endswith(('.png', '.jpg', '.jpeg')):
+            file_path = os.path.join(folder_path, file)
+            file_stats = os.stat(file_path)
+            image_files.append({
+                "filename": file,
+                "size_bytes": file_stats.st_size,
+                "modified_time": time.ctime(file_stats.st_mtime),
+                "url": f"/images/{course_folder}/{file}"
+            })
+    
+    return {
+        "course_folder": course_folder,
+        "total_images": len(image_files),
+        "images": image_files
+    }
+
+@app.get("/courses")
+async def list_all_courses():
+    """
+    List all available course folders with their image counts
+    """
+    if not os.path.exists(FRAMES_OUTPUT_FOLDER):
+        return {"courses": [], "message": "Frames output folder does not exist yet"}
+    
+    courses = []
+    for folder in os.listdir(FRAMES_OUTPUT_FOLDER):
+        folder_path = os.path.join(FRAMES_OUTPUT_FOLDER, folder)
+        if os.path.isdir(folder_path):
+            # Count image files
+            image_count = len([f for f in os.listdir(folder_path) 
+                             if f.lower().endswith(('.png', '.jpg', '.jpeg'))])
+            courses.append({
+                "course_folder": folder,
+                "image_count": image_count,
+                "images_url": f"/images/{folder}",
+                "sample_image_url": f"/images/{folder}/0001.png" if image_count > 0 else None
+            })
+    
+    return {
+        "total_courses": len(courses),
+        "courses": courses
+    }
+
+# ===== EXISTING ANALYSIS ENDPOINTS =====
+
 @app.get("/analysis-data")
 async def list_analysis_data():
     """List all available analysis JSON files"""
@@ -257,6 +349,7 @@ if __name__ == "__main__":
     
     # Ensure the analysis output folder exists
     os.makedirs(ANALYSIS_OUTPUT_FOLDER, exist_ok=True)
+    os.makedirs(FRAMES_OUTPUT_FOLDER, exist_ok=True)
     
     uvicorn.run(
         app, 
@@ -264,4 +357,5 @@ if __name__ == "__main__":
         port=8000, 
         log_level="info",
         reload=False  # Set to False for production
-    )
+    )
+