v1.0

app.py

@@ -0,0 +1,91 @@
+import os
+import subprocess
+from flask import Flask, request, jsonify, send_from_directory
+from werkzeug.utils import secure_filename
+
+app = Flask(__name__)
+
+UPLOAD_FOLDER = "inputs/whole_imgs"
+RESULT_FOLDER = "results/restored_imgs"
+BASE_URL = "https://yut-ka-gfpgan-40e7.twc1.net"
+ALLOWED_EXTENSIONS = {"png", "jpg", "jpeg"}
+
+os.makedirs(UPLOAD_FOLDER, exist_ok=True)
+os.makedirs(RESULT_FOLDER, exist_ok=True)
+
+def allowed_file(filename):
+    return '.' in filename and filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS
+
+@app.route('/results/restored_imgs/<filename>')
+def serve_restored_image(filename):
+    return send_from_directory(RESULT_FOLDER, filename)
+
+@app.route("/restore", methods=["POST"])
+def restore():
+    if 'image' not in request.files:
+        return jsonify({"error": "Нет файла image в запросе"}), 400
+
+    file = request.files['image']
+    if file.filename == '':
+        return jsonify({"error": "Имя файла пустое"}), 400
+
+    if file and allowed_file(file.filename):
+        filename = secure_filename(file.filename)
+
+        # Очистка папок
+        for f in os.listdir(UPLOAD_FOLDER):
+            os.remove(os.path.join(UPLOAD_FOLDER, f))
+        for f in os.listdir(RESULT_FOLDER):
+            os.remove(os.path.join(RESULT_FOLDER, f))
+
+        # Сохранение оригинала
+        filepath = os.path.join(UPLOAD_FOLDER, filename)
+        file.save(filepath)
+
+
+        try:
+            # === GFPGAN v1.4 ===
+            result1 = subprocess.run([
+                "python", "inference_gfpgan.py",
+                "-i", UPLOAD_FOLDER,
+                "-o", "results",
+                "-v", "1.4",
+                "--bg_upsampler", "realesrgan",
+                "-s", "2"
+            ], capture_output=True, text=True)
+
+            if result1.returncode != 0:
+                return jsonify({"error": "Ошибка запуска GFPGAN v1.4", "stderr": result1.stderr}), 500
+
+            step1_file = os.listdir(RESULT_FOLDER)[0]
+            step1_filename = "restored_step1_" + filename
+            step1_output_path = os.path.join(RESULT_FOLDER, step1_filename)
+            os.rename(os.path.join(RESULT_FOLDER, step1_file), step1_output_path)
+
+            # === GFPGAN RestoreFormer ===
+            result2 = subprocess.run([
+                "python", "inference_gfpgan.py",
+                "-i", UPLOAD_FOLDER,
+                "-o", "results",
+                "-v", "RestoreFormer",
+                "--bg_upsampler", "realesrgan",
+                "-s", "2"
+            ], capture_output=True, text=True)
+
+            if result2.returncode != 0:
+                return jsonify({"error": "Ошибка запуска RestoreFormer", "stderr": result2.stderr}), 500
+
+            step2_file = os.listdir(RESULT_FOLDER)[0]
+            final_filename = "restored_final_" + filename
+            final_output_path = os.path.join(RESULT_FOLDER, final_filename)
+            os.rename(os.path.join(RESULT_FOLDER, step2_file), final_output_path)
+
+            return jsonify({
+                "step1_image": f"{BASE_URL}/results/restored_imgs/{final_filename}",
+                "final_image": f"{BASE_URL}/results/restored_imgs/{filename}"
+            })
+
+        except Exception as e:
+            return jsonify({"error": f"Ошибка обработки: {str(e)}"}), 500
+
+    return jsonify({"error": "Формат файла не поддерживается"}), 400

requirements.txt

@@ -1,12 +1,16 @@
+# Минимально проверенные совместимые версии
+torch==2.0.1
+torchvision==0.15.2
+
+# Остальные зависимости
 basicsr>=1.4.2
 facexlib>=0.2.5
 lmdb
-numpy
+numpy<2
 opencv-python
 pyyaml
 scipy
 tb-nightly
-torch>=1.7
-torchvision
 tqdm
 yapf
+flask

setup.py

@@ -2,6 +2,7 @@
 
 from setuptools import find_packages, setup
 
+
 import os
 import subprocess
 import time