Update app.py

app.py

@@ -623,24 +623,79 @@ def run_inference(process_id, input_image, upscale_factor, seed, num_inference_s
     app.config['image_outputs'][process_id] = image_base64
     logger.info("Inference completed for process_id: %s", process_id)
 
+# @app.route('/infer', methods=['POST'])
+# def infer():
+#     data = request.json
+#     seed = data.get("seed", 42)
+#     randomize_seed = data.get("randomize_seed", True)
+#     num_inference_steps = data.get("num_inference_steps", 28)
+#     upscale_factor = data.get("upscale_factor", 4)
+#     controlnet_conditioning_scale = data.get("controlnet_conditioning_scale", 0.6)
+
+#     # Randomize seed if specified
+#     if randomize_seed:
+#         seed = random.randint(0, MAX_SEED)
+#         logger.info("Seed randomized to: %d", seed)
+
+#     # Load and process the input image
+#     input_image_data = base64.b64decode(data['input_image'])
+#     input_image = Image.open(io.BytesIO(input_image_data))
+
+#     # Create a unique process ID for this request
+#     process_id = str(random.randint(1000, 9999))
+#     logger.info("Process started with process_id: %s", process_id)
+
+#     # Set the status to 'in_progress'
+#     app.config['image_outputs'][process_id] = None
+
+    # # Run the inference in a separate thread
+    # executor.submit(run_inference, process_id, input_image, upscale_factor, seed, num_inference_steps, controlnet_conditioning_scale)
+
+    # # Return the process ID
+    # return jsonify({
+    #     "process_id": process_id,
+    #     "message": "Processing started"
+    # })
+
 @app.route('/infer', methods=['POST'])
 def infer():
-    data = request.json
-    seed = data.get("seed", 42)
-    randomize_seed = data.get("randomize_seed", True)
-    num_inference_steps = data.get("num_inference_steps", 28)
-    upscale_factor = data.get("upscale_factor", 4)
-    controlnet_conditioning_scale = data.get("controlnet_conditioning_scale", 0.6)
+    # Check if the file was provided in the form-data
+    if 'input_image' not in request.files:
+        logger.error("No image file provided in request.")
+        return jsonify({
+            "status": "error",
+            "message": "No input_image file provided"
+        }), 400
+
+    # Get the uploaded image file from the request
+    file = request.files['input_image']
+
+    # Check if a file was uploaded
+    if file.filename == '':
+        logger.error("No selected file in form-data.")
+        return jsonify({
+            "status": "error",
+            "message": "No selected file"
+        }), 400
+
+    # Convert the image to Base64 for internal processing
+    input_image = Image.open(file)
+    buffered = io.BytesIO()
+    input_image.save(buffered, format="JPEG")
+    #input_image_base64 = base64.b64encode(buffered.getvalue()).decode("utf-8")
+
+    # Retrieve additional parameters from the request (if any)
+    seed = request.form.get("seed", 42, type=int)
+    randomize_seed = request.form.get("randomize_seed", 'true').lower() == 'true'
+    num_inference_steps = request.form.get("num_inference_steps", 28, type=int)
+    upscale_factor = request.form.get("upscale_factor", 4, type=int)
+    controlnet_conditioning_scale = request.form.get("controlnet_conditioning_scale", 0.6, type=float)
 
     # Randomize seed if specified
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
         logger.info("Seed randomized to: %d", seed)
 
-    # Load and process the input image
-    input_image_data = base64.b64decode(data['input_image'])
-    input_image = Image.open(io.BytesIO(input_image_data))
-
     # Create a unique process ID for this request
     process_id = str(random.randint(1000, 9999))
     logger.info("Process started with process_id: %s", process_id)
@@ -657,6 +712,7 @@ def infer():
         "message": "Processing started"
     })
 
+
 # Modify status endpoint to receive process_id in request body
 @app.route('/status', methods=['POST'])
 def status():