Create app.py

app.py

@@ -0,0 +1,61 @@
+from flask import Flask, request, jsonify
+import cv2
+import mediapipe as mp
+import numpy as np
+from PIL import Image
+import base64
+import io
+
+app = Flask(__name__)
+
+# MediaPipe Pose
+mp_pose = mp.solutions.pose
+pose = mp_pose.Pose(static_image_mode=False, min_detection_confidence=0.5)
+mp_drawing = mp.solutions.drawing_utils
+
+# Load dress
+dress_img = cv2.imread("dress.png", cv2.IMREAD_UNCHANGED)
+
+def overlay_dress(frame, dress, landmarks):
+    if landmarks is not None:
+        h, w, _ = frame.shape
+        def to_pixel(lm):
+            return int(lm.x * w), int(lm.y * h)
+        left_shoulder = to_pixel(landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value])
+        right_shoulder = to_pixel(landmarks[mp_pose.PoseLandmark.RIGHT_SHOULDER.value])
+        left_hip = to_pixel(landmarks[mp_pose.PoseLandmark.LEFT_HIP.value])
+        right_hip = to_pixel(landmarks[mp_pose.PoseLandmark.RIGHT_HIP.value])
+        dress_width = int(np.linalg.norm(np.array(left_shoulder)-np.array(right_shoulder))*1.8)
+        top_shoulder_y = min(left_shoulder[1], right_shoulder[1])
+        bottom_hip_y = max(left_hip[1], right_hip[1])
+        dress_height = int((bottom_hip_y - top_shoulder_y)*1.2)
+        center_x = (left_shoulder[0]+right_shoulder[0])//2
+        x1 = max(center_x - dress_width//2,0)
+        y1 = max(top_shoulder_y - 30,0)
+        x2 = min(x1 + dress_width, w)
+        y2 = min(y1 + dress_height, h)
+        dress_resized = cv2.resize(dress, (x2-x1, y2-y1), interpolation=cv2.INTER_AREA)
+        if dress_resized.shape[2]==4:
+            alpha_s = dress_resized[:,:,3]/255.0
+            alpha_l = 1.0 - alpha_s
+            for c in range(3):
+                frame[y1:y2,x1:x2,c] = alpha_s*dress_resized[:,:,c] + alpha_l*frame[y1:y2,x1:x2,c]
+    return frame
+
+@app.route("/tryon", methods=["POST"])
+def tryon():
+    data = request.json["image"]
+    img_bytes = base64.b64decode(data.split(",")[1])
+    img = Image.open(io.BytesIO(img_bytes)).convert("RGB")
+    frame = cv2.cvtColor(np.array(img), cv2.COLOR_RGB2BGR)
+    results = pose.process(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
+    landmarks = results.pose_landmarks.landmark if results.pose_landmarks else None
+    frame = overlay_dress(frame, dress_img, landmarks)
+    if results.pose_landmarks:
+        mp_drawing.draw_landmarks(frame, results.pose_landmarks, mp_pose.POSE_CONNECTIONS)
+    _, buffer = cv2.imencode(".jpg", frame)
+    img_base64 = "data:image/jpeg;base64," + base64.b64encode(buffer).decode()
+    return jsonify({"image": img_base64})
+
+if __name__=="__main__":
+    app.run(host="0.0.0.0", port=5000)