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import os |
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import time |
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from concurrent.futures import ThreadPoolExecutor |
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import numpy as np |
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from sklearn.cluster import KMeans |
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from flask import Flask, request, send_from_directory, jsonify, abort |
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from flask_cors import CORS |
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def select_step_range(start, end, embeddings_section): |
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kmeans = KMeans(n_clusters=1).fit(embeddings_section) |
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center = kmeans.cluster_centers_[0] |
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distances = np.linalg.norm(embeddings_section - center, axis=1) |
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selected_step = start + np.argmin(distances) |
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return int(selected_step) |
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def select_steps_v2( |
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num_steps, |
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time_embeddings, |
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total_steps=1000, |
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): |
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interval = total_steps / num_steps |
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selected_steps = [] |
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with ThreadPoolExecutor(max_workers=4) as executor: |
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futures = [] |
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for i in range(num_steps): |
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start = int(i * interval) |
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end = int((i + 1) * interval) |
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embeddings_section = time_embeddings[start:end] |
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futures.append( |
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executor.submit(select_step_range, start, end, embeddings_section) |
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) |
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for future in futures: |
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selected_steps.append(future.result()) |
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return selected_steps |
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app = Flask(__name__) |
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CORS(app, resources={r"/*": {"origins": "*"}}) |
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@app.route("/") |
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def index(): |
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return send_from_directory(".", "index.html") |
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@app.route("/process_map", methods=["GET"]) |
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def process(): |
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start_time = time.time() |
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input_path = request.args.get("input_path") |
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num_steps = request.args.get("num_steps", "0") |
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if not input_path or not num_steps: |
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abort( |
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400, |
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description="Missing query parameters: input_path and num_steps are required.", |
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) |
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input_path = ( |
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"data" + input_path.split("data")[1] if "data" in input_path else input_path |
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) |
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input_path = input_path[1:] if input_path.startswith("/") else input_path |
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try: |
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num_steps = int(num_steps) |
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except ValueError: |
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abort(400, description="Invalid parameter: num_steps must be an integer.") |
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try: |
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time_embeddings = np.load(input_path) |
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selected_steps = [] |
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if num_steps != 0: |
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time_embeddings_shape = np.asarray(time_embeddings).shape |
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if len(time_embeddings_shape) == 4: |
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time_embeddings = time_embeddings.squeeze(1).squeeze(1) |
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selected_steps = select_steps_v2(num_steps, time_embeddings) |
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selected_steps = sorted(selected_steps, reverse=True) |
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selected_steps = [str(step) for step in selected_steps] |
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except Exception as e: |
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abort(500, description=str(e)) |
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result = { |
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"input_path": input_path, |
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"num_steps": num_steps, |
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"message": "Processing completed successfully.", |
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"time_embeddings": str(time_embeddings.shape), |
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"selected_steps": selected_steps, |
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"time_cost": time.time() - start_time, |
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} |
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return jsonify(result) |
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@app.route("/<path:filename>") |
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def serve_file(filename): |
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if os.path.exists(filename): |
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return send_from_directory(".", filename) |
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else: |
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abort(404) |
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if __name__ == "__main__": |
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app.run(debug=True) |
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